ACM Knowledge Discovery and Data Mining, KDD 2015


Title/Authors Title Research Artifacts
[?] A research artifact is any by-product of a research project that is not directly included in the published research paper. In Computer Science research this is often source code and data sets, but it could also be media, documentation, inputs to proof assistants, shell-scripts to run experiments, etc.
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Collective Spammer Detection in Evolving Multi-Relational Social Networks

Shobeir Fakhraei, James R. Foulds, Madhusudana V. S. Shashanka, Lise Getoor

Collective Spammer Detection in Evolving Multi-Relational Social Networks

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Stream Sampling for Frequency Cap Statistics

Edith Cohen

Stream Sampling for Frequency Cap Statistics

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MASCOT: Memory-efficient and Accurate Sampling for Counting Local Triangles in Graph Streams

Yongsub Lim, U. Kang

MASCOT: Memory-efficient and Accurate Sampling for Counting Local Triangles in Graph Streams

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Structured Hedging for Resource Allocations with Leverage

Nicholas Johnson, Arindam Banerjee

Structured Hedging for Resource Allocations with Leverage

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Extreme States Distribution Decomposition Method for Search Engine Online Evaluation

Kirill Nikolaev, Alexey Drutsa, Ekaterina Gladkikh, Alexander Ulianov, Gleb Gusev, Pavel Serdyukov

Extreme States Distribution Decomposition Method for Search Engine Online Evaluation

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An Effective Marketing Strategy for Revenue Maximization with a Quantity Constraint

Ya-Wen Teng, Chih-Hua Tai, Philip S. Yu, Ming-Syan Chen

An Effective Marketing Strategy for Revenue Maximization with a Quantity Constraint

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Inferring Air Quality for Station Location Recommendation Based on Urban Big Data

Hsun-Ping Hsieh, Shou-De Lin, Yu Zheng

Inferring Air Quality for Station Location Recommendation Based on Urban Big Data

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Predicting Ambulance Demand: a Spatio-Temporal Kernel Approach

Zhengyi Zhou, David S. Matteson

Predicting Ambulance Demand: a Spatio-Temporal Kernel Approach

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Transitive Transfer Learning

Ben Tan, Yangqiu Song, Erheng Zhong, Qiang Yang

Transitive Transfer Learning

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Petuum: A New Platform for Distributed Machine Learning on Big Data

Eric P. Xing, Qirong Ho, Wei Dai, Jin Kyu Kim, Jinliang Wei, Seunghak Lee, Xun Zheng, Pengtao Xie, Abhimanu Kumar, Yaoliang Yu

Petuum: A New Platform for Distributed Machine Learning on Big Data

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Real Time Recommendations from Connoisseurs

Noriaki Kawamae

Real Time Recommendations from Connoisseurs

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From Infrastructure to Culture: A/B Testing Challenges in Large Scale Social Networks

Ya Xu, Nanyu Chen, Addrian Fernandez, Omar Sinno, Anmol Bhasin

From Infrastructure to Culture: A/B Testing Challenges in Large Scale Social Networks

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LINKAGE: An Approach for Comprehensive Risk Prediction for Care Management

Zhaonan Sun, Fei Wang, Jianying Hu

LINKAGE: An Approach for Comprehensive Risk Prediction for Care Management

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Predicting Winning Price in Real Time Bidding with Censored Data

Wush Chi-Hsuan Wu, Mi-Yen Yeh, Ming-Syan Chen

Predicting Winning Price in Real Time Bidding with Censored Data

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Accelerated Alternating Direction Method of Multipliers

Mojtaba Kadkhodaie, Konstantina Christakopoulou, Maziar Sanjabi, Arindam Banerjee

Accelerated Alternating Direction Method of Multipliers

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Deep Learning Architecture with Dynamically Programmed Layers for Brain Connectome Prediction

Vivek Veeriah, Rohit Durvasula, Guo-Jun Qi

Deep Learning Architecture with Dynamically Programmed Layers for Brain Connectome Prediction

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E-commerce in Your Inbox: Product Recommendations at Scale

Mihajlo Grbovic, Vladan Radosavljevic, Nemanja Djuric, Narayan Bhamidipati, Jaikit Savla, Varun Bhagwan, Doug Sharp

E-commerce in Your Inbox: Product Recommendations at Scale

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Multi-Task Learning for Spatio-Temporal Event Forecasting

Liang Zhao, Qian Sun, Jieping Ye, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan

Multi-Task Learning for Spatio-Temporal Event Forecasting

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Dynamically Modeling Patient's Health State from Electronic Medical Records: A Time Series Approach

Karla L. Caballero Barajas, Ram Akella

Dynamically Modeling Patient's Health State from Electronic Medical Records: A Time Series Approach

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A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes

Himabindu Lakkaraju, Everaldo Aguiar, Carl Shan, David Miller, Nasir Bhanpuri, Rayid Ghani, Kecia L. Addison

A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes

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Traffic Measurement and Route Recommendation System for Mass Rapid Transit (MRT)

Thomas Holleczek, Dang The Anh, Shanyang Yin, Yunye Jin, Spiros Antonatos, Han Leong Goh, Samantha Low, Amy Shi Nash

Traffic Measurement and Route Recommendation System for Mass Rapid Transit (MRT)

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Transfer Learning for Bilingual Content Classification

Qian Sun, Mohammad Shafkat Amin, Baoshi Yan, Craig Martell, Vita Markman, Anmol Bhasin, Jieping Ye

Transfer Learning for Bilingual Content Classification

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Data Science from the Lab to the Field to the Enterprise

Christopher White

Data Science from the Lab to the Field to the Enterprise

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Reciprocity in Social Networks with Capacity Constraints

Bo Jiang, Zhi-Li Zhang, Don Towsley

Reciprocity in Social Networks with Capacity Constraints

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Gender and Interest Targeting for Sponsored Post Advertising at Tumblr

Mihajlo Grbovic, Vladan Radosavljevic, Nemanja Djuric, Narayan Bhamidipati, Ananth Nagarajan

Gender and Interest Targeting for Sponsored Post Advertising at Tumblr

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SAME but Different: Fast and High Quality Gibbs Parameter Estimation

Huasha Zhao, Biye Jiang, John F. Canny, Bobby Jaros

SAME but Different: Fast and High Quality Gibbs Parameter Estimation

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Assembler: Efficient Discovery of Spatial Co-evolving Patterns in Massive Geo-sensory Data

Chao Zhang, Yu Zheng, Xiuli Ma, Jiawei Han

Assembler: Efficient Discovery of Spatial Co-evolving Patterns in Massive Geo-sensory Data

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Web Personalization and Recommender Systems

Shlomo Berkovsky, Jill Freyne

Web Personalization and Recommender Systems

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Dimensionality Reduction Via Graph Structure Learning

Qi Mao, Li Wang, Steve Goodison, Yijun Sun

Dimensionality Reduction Via Graph Structure Learning

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Fast and Robust Parallel SGD Matrix Factorization

Jinoh Oh, Wook-Shin Han, Hwanjo Yu, Xiaoqian Jiang

Fast and Robust Parallel SGD Matrix Factorization

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Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis

Wenlu Zhang, Rongjian Li, Tao Zeng, Qian Sun, Sudhir Kumar, Jieping Ye, Shuiwang Ji

Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis

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Dynamic Hierarchical Classification for Patient Risk-of-Readmission

Senjuti Basu Roy, Ankur Teredesai, Kiyana Zolfaghar, Rui Liu, David Hazel, Stacey Newman, Albert Marinez

Dynamic Hierarchical Classification for Patient Risk-of-Readmission

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Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing

Felipe Llinares-López, Mahito Sugiyama, Laetitia Papaxanthos, Karsten M. Borgwardt

Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing

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Life-stage Prediction for Product Recommendation in E-commerce

Peng Jiang, Yadong Zhu, Yi Zhang, Quan Yuan

Life-stage Prediction for Product Recommendation in E-commerce

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Online Topic-based Social Influence Analysis for the Wimbledon Championships

Varun R. Embar, Indrajit Bhattacharya, Vinayaka Pandit, Roman Vaculín

Online Topic-based Social Influence Analysis for the Wimbledon Championships

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Large Scale Distributed Data Science using Apache Spark

James G. Shanahan, Laing Dai

Large Scale Distributed Data Science using Apache Spark

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Model Multiple Heterogeneity via Hierarchical Multi-Latent Space Learning

Pei Yang, Jingrui He

Model Multiple Heterogeneity via Hierarchical Multi-Latent Space Learning

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Going In-Depth: Finding Longform on the Web

Virginia Smith, Miriam Connor, Isabelle Stanton

Going In-Depth: Finding Longform on the Web

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ClusType: Effective Entity Recognition and Typing by Relation Phrase-Based Clustering

Xiang Ren, Ahmed El-Kishky, Chi Wang, Fangbo Tao, Clare R. Voss, Jiawei Han

ClusType: Effective Entity Recognition and Typing by Relation Phrase-Based Clustering

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Automatic Entity Recognition and Typing from Massive Text Corpora: A Phrase and Network Mining Approach

Xiang Ren, Ahmed El-Kishky, Chi Wang, Jiawei Han

Automatic Entity Recognition and Typing from Massive Text Corpora: A Phrase and Network Mining Approach

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Discovery of Glaucoma Progressive Patterns Using Hierarchical MDL-Based Clustering

Shigeru Maya, Kai Morino, Hiroshi Murata, Ryo Asaoka, Kenji Yamanishi

Discovery of Glaucoma Progressive Patterns Using Hierarchical MDL-Based Clustering

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Stochastic Divergence Minimization for Online Collapsed Variational Bayes Zero Inference of Latent Dirichlet Allocation

Issei Sato, Hiroshi Nakagawa

Stochastic Divergence Minimization for Online Collapsed Variational Bayes Zero Inference of Latent Dirichlet Allocation

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When-To-Post on Social Networks

Nemanja Spasojevic, Zhisheng Li, Adithya Rao, Prantik Bhattacharyya

When-To-Post on Social Networks

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Collective Opinion Spam Detection: Bridging Review Networks and Metadata

Shebuti Rayana, Leman Akoglu

Collective Opinion Spam Detection: Bridging Review Networks and Metadata

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TimeMachine: Timeline Generation for Knowledge-Base Entities

Tim Althoff, Xin Luna Dong, Kevin Murphy, Safa Alai, Van Dang, Wei Zhang

TimeMachine: Timeline Generation for Knowledge-Base Entities

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Accelerating Dynamic Time Warping Clustering with a Novel Admissible Pruning Strategy

Nurjahan Begum, Liudmila Ulanova, Jun Wang, Eamonn J. Keogh

Accelerating Dynamic Time Warping Clustering with a Novel Admissible Pruning Strategy

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Anatomical Annotations for Drosophila Gene Expression Patterns via Multi-Dimensional Visual Descriptors Integration: Multi-Dimensional Feature Learning

Hongchang Gao, Lin Yan, Weidong Cai, Heng Huang

Anatomical Annotations for Drosophila Gene Expression Patterns via Multi-Dimensional Visual Descriptors Integration: Multi-Dimensional Feature Learning

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Predictive Approaches for Low-Cost Preventive Medicine Program in Developing Countries

Yukino Baba, Hisashi Kashima, Yasunobu Nohara, Eiko Kai, Partha Pratim Ghosh, Rafiqul Islam Maruf, Ashir Ahmed, Masahiro Kuroda, Sozo Inoue, Tatsuo Hiramatsu, Michio Kimura, Shuji Shimizu, Kunihisa Kobayashi, Koji Tsuda, Masashi Sugiyama, Mathieu Blondel, Naonori Ueda, Masaru Kitsuregawa, Naoki Nakashima

Predictive Approaches for Low-Cost Preventive Medicine Program in Developing Countries

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Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling

Michael Mitzenmacher, Jakub Pachocki, Richard Peng, Charalampos E. Tsourakakis, Shen Chen Xu

Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling

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Spectral Ensemble Clustering

Hongfu Liu, Tongliang Liu, Junjie Wu, Dacheng Tao, Yun Fu

Spectral Ensemble Clustering

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Cuckoo Linear Algebra

Li Zhou, David G. Andersen, Mu Li, Alexander J. Smola

Cuckoo Linear Algebra

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Non-transitive Hashing with Latent Similarity Components

Mingdong Ou, Peng Cui, Fei Wang, Jun Wang, Wenwu Zhu

Non-transitive Hashing with Latent Similarity Components

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Big Data Analytics: Optimization and Randomization

Tianbao Yang, Qihang Lin, Rong Jin

Big Data Analytics: Optimization and Randomization

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Adaptation Algorithm and Theory Based on Generalized Discrepancy

Corinna Cortes, Mehryar Mohri, Andres Muñoz Medina

Adaptation Algorithm and Theory Based on Generalized Discrepancy

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Community Detection based on Distance Dynamics

Junming Shao, Zhichao Han, Qinli Yang, Tao Zhou

Community Detection based on Distance Dynamics

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Monitoring Least Squares Models of Distributed Streams

Moshe Gabel, Daniel Keren, Assaf Schuster

Monitoring Least Squares Models of Distributed Streams

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From Group to Individual Labels Using Deep Features

Dimitrios Kotzias, Misha Denil, Nando de Freitas, Padhraic Smyth

From Group to Individual Labels Using Deep Features

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On the Formation of Circles in Co-authorship Networks

Tanmoy Chakraborty, Sikhar Patranabis, Pawan Goyal, Animesh Mukherjee

On the Formation of Circles in Co-authorship Networks

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Reducing the Unlabeled Sample Complexity of Semi-Supervised Multi-View Learning

Chao Lan, Jun Huan

Reducing the Unlabeled Sample Complexity of Semi-Supervised Multi-View Learning

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Unsupervised Feature Selection with Adaptive Structure Learning

Liang Du, Yi-Dong Shen

Unsupervised Feature Selection with Adaptive Structure Learning

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Data, Knowledge and Discovery: Machine Learning meets Natural Science

Hugh Durrant-Whyte

Data, Knowledge and Discovery: Machine Learning meets Natural Science

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Big Data System for Analyzing Risky Procurement Entities

Amit Dhurandhar, Bruce Graves, Rajesh Kumar Ravi, Gopikrishnan Maniachari, Markus Ettl

Big Data System for Analyzing Risky Procurement Entities

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Turn Waste into Wealth: On Simultaneous Clustering and Cleaning over Dirty Data

Shaoxu Song, Chunping Li, Xiaoquan Zhang

Turn Waste into Wealth: On Simultaneous Clustering and Cleaning over Dirty Data

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Whither Social Networks for Web Search?

Rakesh Agrawal, Behzad Golshan, Evangelos E. Papalexakis

Whither Social Networks for Web Search?

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Trading Interpretability for Accuracy: Oblique Treed Sparse Additive Models

Jialei Wang, Ryohei Fujimaki, Yosuke Motohashi

Trading Interpretability for Accuracy: Oblique Treed Sparse Additive Models

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Portraying Collective Spatial Attention in Twitter

Émilien Antoine, Adam Jatowt, Shoko Wakamiya, Yukiko Kawai, Toyokazu Akiyama

Portraying Collective Spatial Attention in Twitter

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Learning with Similarity Functions on Graphs using Matchings of Geometric Embeddings

Fredrik D. Johansson, Devdatt P. Dubhashi

Learning with Similarity Functions on Graphs using Matchings of Geometric Embeddings

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Rubik: Knowledge Guided Tensor Factorization and Completion for Health Data Analytics

Yichen Wang, Robert Chen, Joydeep Ghosh, Joshua C. Denny, Abel N. Kho, You Chen, Bradley A. Malin, Jimeng Sun

Rubik: Knowledge Guided Tensor Factorization and Completion for Health Data Analytics

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Early Identification of Violent Criminal Gang Members

Elham Shaabani, Ashkan Aleali, Paulo Shakarian, John Bertetto

Early Identification of Violent Criminal Gang Members

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CoupledLP: Link Prediction in Coupled Networks

Yuxiao Dong, Jing Zhang, Jie Tang, Nitesh V. Chawla, Bai Wang

CoupledLP: Link Prediction in Coupled Networks

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PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks

Jian Tang, Meng Qu, Qiaozhu Mei

PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks

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State-Driven Dynamic Sensor Selection and Prediction with State-Stacked Sparseness

Guo-Jun Qi, Charu Aggarwal, Deepak S. Turaga, Daby M. Sow, Phil Anno

State-Driven Dynamic Sensor Selection and Prediction with State-Stacked Sparseness

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Leveraging Knowledge Bases for Contextual Entity Exploration

Joonseok Lee, Ariel Fuxman, Bo Zhao, Yuanhua Lv

Leveraging Knowledge Bases for Contextual Entity Exploration

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Deep Graph Kernels

Pinar Yanardag, S. V. N. Vishwanathan

Deep Graph Kernels

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Organizational Chart Inference

Jiawei Zhang, Philip S. Yu, Yuanhua Lv

Organizational Chart Inference

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Dynamic Matrix Factorization with Priors on Unknown Values

Robin Devooght, Nicolas Kourtellis, Amin Mantrach

Dynamic Matrix Factorization with Priors on Unknown Values

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Robust Treecode Approximation for Kernel Machines

William B. March, Bo Xiao, Sameer Tharakan, Chenhan D. Yu, George Biros

Robust Treecode Approximation for Kernel Machines

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Clouded Intelligence

Joseph Sirosh

Clouded Intelligence

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BatchRank: A Novel Batch Mode Active Learning Framework for Hierarchical Classification

Shayok Chakraborty, Vineeth Nallure Balasubramanian, Adepu Ravi Sankar, Sethuraman Panchanathan, Jieping Ye

BatchRank: A Novel Batch Mode Active Learning Framework for Hierarchical Classification

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Online Influence Maximization

Siyu Lei, Silviu Maniu, Luyi Mo, Reynold Cheng, Pierre Senellart

Online Influence Maximization

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Simultaneous Modeling of Multiple Diseases for Mortality Prediction in Acute Hospital Care

Nozomi Nori, Hisashi Kashima, Kazuto Yamashita, Hiroshi Ikai, Yuichi Imanaka

Simultaneous Modeling of Multiple Diseases for Mortality Prediction in Acute Hospital Care

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Analyzing Invariants in Cyber-Physical Systems using Latent Factor Regression

Marjan Momtazpour, Jinghe Zhang, Saifur Rahman, Ratnesh K. Sharma, Naren Ramakrishnan

Analyzing Invariants in Cyber-Physical Systems using Latent Factor Regression

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Gas Concentration Reconstruction for Coal-Fired Boilers Using Gaussian Process

Chao Yuan, Matthias Behmann, Bernhard Meerbeck

Gas Concentration Reconstruction for Coal-Fired Boilers Using Gaussian Process

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Predicting Serves in Tennis using Style Priors

Xinyu Wei, Patrick Lucey, Stuart Morgan, Peter Carr, Machar Reid, Sridha Sridharan

Predicting Serves in Tennis using Style Priors

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Real-Time Bid Prediction using Thompson Sampling-Based Expert Selection

Elena Ikonomovska, Sina Jafarpour, Ali Dasdan

Real-Time Bid Prediction using Thompson Sampling-Based Expert Selection

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Optimizing Marketing Impact through Data Driven Decisioning

Anil Kamath

Optimizing Marketing Impact through Data Driven Decisioning

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Optimal Kernel Group Transformation for Exploratory Regression Analysis and Graphics

Pan Chao, Qiming Huang, Michael Zhu

Optimal Kernel Group Transformation for Exploratory Regression Analysis and Graphics

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Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams

Nan Du, Mehrdad Farajtabar, Amr Ahmed, Alexander J. Smola, Le Song

Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams

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Focusing on the Long-term: It's Good for Users and Business

Henning Hohnhold, Deirdre O'Brien, Diane Tang

Focusing on the Long-term: It's Good for Users and Business

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Predicting Voice Elicited Emotions

Ying Li, Jose D. Contreras, Luis J. Salazar

Predicting Voice Elicited Emotions

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Efficient PageRank Tracking in Evolving Networks

Naoto Ohsaka, Takanori Maehara, Ken-ichi Kawarabayashi

Efficient PageRank Tracking in Evolving Networks

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Scalable Blocking for Privacy Preserving Record Linkage

Alexandros Karakasidis, Georgia Koloniari, Vassilios S. Verykios

Scalable Blocking for Privacy Preserving Record Linkage

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Probabilistic Modeling of a Sales Funnel to Prioritize Leads

Brendan Andrew Duncan, Charles Peter Elkan

Probabilistic Modeling of a Sales Funnel to Prioritize Leads

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Entity Matching across Heterogeneous Sources

Yang Yang, Yizhou Sun, Jie Tang, Bo Ma, Juan-Zi Li

Entity Matching across Heterogeneous Sources

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Performance Modeling and Scalability Optimization of Distributed Deep Learning Systems

Feng Yan, Olatunji Ruwase, Yuxiong He, Trishul M. Chilimbi

Performance Modeling and Scalability Optimization of Distributed Deep Learning Systems

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SEISMIC: A Self-Exciting Point Process Model for Predicting Tweet Popularity

Qingyuan Zhao, Murat A. Erdogdu, Hera Y. He, Anand Rajaraman, Jure Leskovec

SEISMIC: A Self-Exciting Point Process Model for Predicting Tweet Popularity

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Graph-Based User Behavior Modeling: From Prediction to Fraud Detection

Alex Beutel, Leman Akoglu, Christos Faloutsos

Graph-Based User Behavior Modeling: From Prediction to Fraud Detection

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A Learning-based Framework to Handle Multi-round Multi-party Influence Maximization on Social Networks

Su-Chen Lin, Shou-De Lin, Ming-Syan Chen

A Learning-based Framework to Handle Multi-round Multi-party Influence Maximization on Social Networks

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Simultaneous Discovery of Common and Discriminative Topics via Joint Nonnegative Matrix Factorization

Hannah Kim, Jaegul Choo, Jingu Kim, Chandan K. Reddy, Haesun Park

Simultaneous Discovery of Common and Discriminative Topics via Joint Nonnegative Matrix Factorization

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Real Estate Ranking via Mixed Land-use Latent Models

Yanjie Fu, Guannan Liu, Spiros Papadimitriou, Hui Xiong, Yong Ge, Hengshu Zhu, Chen Zhu

Real Estate Ranking via Mixed Land-use Latent Models

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Who Supported Obama in 2012?: Ecological Inference through Distribution Regression

Seth R. Flaxman, Yu-Xiang Wang, Alexander J. Smola

Who Supported Obama in 2012?: Ecological Inference through Distribution Regression

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Edge-Weighted Personalized PageRank: Breaking A Decade-Old Performance Barrier

Wenlei Xie, David Bindel, Alan J. Demers, Johannes Gehrke

Edge-Weighted Personalized PageRank: Breaking A Decade-Old Performance Barrier

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Certifying and Removing Disparate Impact

Michael Feldman, Sorelle A. Friedler, John Moeller, Carlos Scheidegger, Suresh Venkatasubramanian

Certifying and Removing Disparate Impact

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An Architecture for Agile Machine Learning in Real-Time Applications

Johann Schleier-Smith

An Architecture for Agile Machine Learning in Real-Time Applications

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Cinema Data Mining: The Smell of Fear

Jörg Wicker, Nicolas Krauter, Bettina Derstorff, Christof Stönner, Efstratios Bourtsoukidis, Thomas Klüpfel, Jonathan Williams, Stefan Kramer

Cinema Data Mining: The Smell of Fear

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Leveraging Social Context for Modeling Topic Evolution

Janani Kalyanam, Amin Mantrach, Diego Sáez-Trumper, Hossein Vahabi, Gert R. G. Lanckriet

Leveraging Social Context for Modeling Topic Evolution

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Diversifying Restricted Boltzmann Machine for Document Modeling

Pengtao Xie, Yuntian Deng, Eric P. Xing

Diversifying Restricted Boltzmann Machine for Document Modeling

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One-Pass Ranking Models for Low-Latency Product Recommendations

Antonino Freno, Martin Saveski, Rodolphe Jenatton, Cédric Archambeau

One-Pass Ranking Models for Low-Latency Product Recommendations

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Scaling Up Stochastic Dual Coordinate Ascent

Kenneth Tran, Saghar Hosseini, Lin Xiao, Thomas Finley, Mikhail Bilenko

Scaling Up Stochastic Dual Coordinate Ascent

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Instance Weighting for Patient-Specific Risk Stratification Models

Jen J. Gong, Thoralf M. Sundt, James D. Rawn, John V. Guttag

Instance Weighting for Patient-Specific Risk Stratification Models

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Data-Driven Activity Prediction: Algorithms, Evaluation Methodology, and Applications

Bryan Minor, Janardhan Rao Doppa, Diane J. Cook

Data-Driven Activity Prediction: Algorithms, Evaluation Methodology, and Applications

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Mining for Causal Relationships: A Data-Driven Study of the Islamic State

Andrew Stanton, Amanda Thart, Ashish Jain, Priyank Vyas, Arpan Chatterjee, Paulo Shakarian

Mining for Causal Relationships: A Data-Driven Study of the Islamic State

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Mining Frequent Itemsets through Progressive Sampling with Rademacher Averages

Matteo Riondato, Eli Upfal

Mining Frequent Itemsets through Progressive Sampling with Rademacher Averages

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A Deep Hybrid Model for Weather Forecasting

Aditya Grover, Ashish Kapoor, Eric Horvitz

A Deep Hybrid Model for Weather Forecasting

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Geo-SAGE: A Geographical Sparse Additive Generative Model for Spatial Item Recommendation

Weiqing Wang, Hongzhi Yin, Ling Chen, Yizhou Sun, Shazia Wasim Sadiq, Xiaofang Zhou

Geo-SAGE: A Geographical Sparse Additive Generative Model for Spatial Item Recommendation

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SCRAM: A Sharing Considered Route Assignment Mechanism for Fair Taxi Route Recommendations

Shiyou Qian, Jian Cao, Frédéric Le Mouël, Issam Sahel, Minglu Li

SCRAM: A Sharing Considered Route Assignment Mechanism for Fair Taxi Route Recommendations

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Facets: Fast Comprehensive Mining of Coevolving High-order Time Series

Yongjie Cai, Hanghang Tong, Wei Fan, Ping Ji, Qing He

Facets: Fast Comprehensive Mining of Coevolving High-order Time Series

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RSC: Mining and Modeling Temporal Activity in Social Media

Alceu Ferraz Costa, Yuto Yamaguchi, Agma Juci Machado Traina, Caetano Traina Jr., Christos Faloutsos

RSC: Mining and Modeling Temporal Activity in Social Media

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How Artificial Intelligence and Big Data Created Rocket Fuel: A Case Study

George John

How Artificial Intelligence and Big Data Created Rocket Fuel: A Case Study

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Exploiting Relevance Feedback in Knowledge Graph Search

Yu Su, Shengqi Yang, Huan Sun, Mudhakar Srivatsa, Sue Kase, Michelle Vanni, Xifeng Yan

Exploiting Relevance Feedback in Knowledge Graph Search

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A Clustering-Based Framework to Control Block Sizes for Entity Resolution

Jeffrey Fisher, Peter Christen, Qing Wang, Erhard Rahm

A Clustering-Based Framework to Control Block Sizes for Entity Resolution

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On the Reliability of Profile Matching Across Large Online Social Networks

Oana Goga, Patrick Loiseau, Robin Sommer, Renata Teixeira, Krishna P. Gummadi

On the Reliability of Profile Matching Across Large Online Social Networks

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Graph Query Reformulation with Diversity

Davide Mottin, Francesco Bonchi, Francesco Gullo

Graph Query Reformulation with Diversity

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Efficient Latent Link Recommendation in Signed Networks

Dongjin Song, David A. Meyer, Dacheng Tao

Efficient Latent Link Recommendation in Signed Networks

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Stock Constrained Recommendation in Tmall

Wenliang Zhong, Rong Jin, Cheng Yang, Xiaowei Yan, Qi Zhang, Qiang Li

Stock Constrained Recommendation in Tmall

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Selective Hashing: Closing the Gap between Radius Search and k-NN Search

Jinyang Gao, H. V. Jagadish, Beng Chin Ooi, Sheng Wang

Selective Hashing: Closing the Gap between Radius Search and k-NN Search

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Improved Bounds on the Dot Product under Random Projection and Random Sign Projection

Ata Kaban

Improved Bounds on the Dot Product under Random Projection and Random Sign Projection

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Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction

Tingyang Xu, Jiangwen Sun, Jinbo Bi

Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction

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Linear Time Samplers for Supervised Topic Models using Compositional Proposals

Xun Zheng, Yaoliang Yu, Eric P. Xing

Linear Time Samplers for Supervised Topic Models using Compositional Proposals

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A PCA-Based Change Detection Framework for Multidimensional Data Streams: Change Detection in Multidimensional Data Streams

Abdulhakim Ali Qahtan, Basma Alharbi, Suojin Wang, Xiangliang Zhang

A PCA-Based Change Detection Framework for Multidimensional Data Streams: Change Detection in Multidimensional Data Streams

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Efficient Long-Term Degradation Profiling in Time Series for Complex Physical Systems

Liudmila Ulanova, Tan Yan, Haifeng Chen, Guofei Jiang, Eamonn J. Keogh, Kai Zhang

Efficient Long-Term Degradation Profiling in Time Series for Complex Physical Systems

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Dense Subgraph Discovery: KDD 2015 tutorial

Aristides Gionis, Charalampos E. Tsourakakis

Dense Subgraph Discovery: KDD 2015 tutorial

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Website Optimization Problem and Its Solutions

Shuhei Iitsuka, Yutaka Matsuo

Website Optimization Problem and Its Solutions

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Locally Densest Subgraph Discovery

Lu Qin, Rong-Hua Li, Lijun Chang, Chengqi Zhang

Locally Densest Subgraph Discovery

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Discerning Tactical Patterns for Professional Soccer Teams: An Enhanced Topic Model with Applications

Qing Wang, Hengshu Zhu, Wei Hu, Zhiyong Shen, Yuan Yao

Discerning Tactical Patterns for Professional Soccer Teams: An Enhanced Topic Model with Applications

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Inside Jokes: Identifying Humorous Cartoon Captions

Dafna Shahaf, Eric Horvitz, Robert Mankoff

Inside Jokes: Identifying Humorous Cartoon Captions

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Modeling User Mobility for Location Promotion in Location-based Social Networks

Wen-Yuan Zhu, Wen-Chih Peng, Ling-Jyh Chen, Kai Zheng, Xiaofang Zhou

Modeling User Mobility for Location Promotion in Location-based Social Networks

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TOPTRAC: Topical Trajectory Pattern Mining

Younghoon Kim, Jiawei Han, Cangzhou Yuan

TOPTRAC: Topical Trajectory Pattern Mining

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An Efficient Semi-Supervised Clustering Algorithm with Sequential Constraints

Jinfeng Yi, Lijun Zhang, Tianbao Yang, Wei Liu, Jun Wang

An Efficient Semi-Supervised Clustering Algorithm with Sequential Constraints

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Flexible and Robust Multi-Network Clustering

Jingchao Ni, Hanghang Tong, Wei Fan, Xiang Zhang

Flexible and Robust Multi-Network Clustering

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Integrating Vertex-centric Clustering with Edge-centric Clustering for Meta Path Graph Analysis

Yang Zhou, Ling Liu, David Buttler

Integrating Vertex-centric Clustering with Edge-centric Clustering for Meta Path Graph Analysis

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Network Lasso: Clustering and Optimization in Large Graphs

David Hallac, Jure Leskovec, Stephen P. Boyd

Network Lasso: Clustering and Optimization in Large Graphs

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Hierarchical Graph-Coupled HMMs for Heterogeneous Personalized Health Data

Kai Fan, Marisa C. Eisenberg, Alison Walsh, Allison Aiello, Katherine A. Heller

Hierarchical Graph-Coupled HMMs for Heterogeneous Personalized Health Data

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Discovery of Meaningful Rules in Time Series

Mohammad Shokoohi-Yekta, Yanping Chen, Bilson J. L. Campana, Bing Hu, Jesin Zakaria, Eamonn J. Keogh

Discovery of Meaningful Rules in Time Series

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Panther: Fast Top-k Similarity Search on Large Networks

Jing Zhang, Jie Tang, Cong Ma, Hanghang Tong, Yu Jing, Juanzi Li

Panther: Fast Top-k Similarity Search on Large Networks

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Promoting Positive Post-Click Experience for In-Stream Yahoo Gemini Users

Mounia Lalmas, Janette Lehmann, Guy Shaked, Fabrizio Silvestri, Gabriele Tolomei

Promoting Positive Post-Click Experience for In-Stream Yahoo Gemini Users

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Annotating Needles in the Haystack without Looking: Product Information Extraction from Emails

Weinan Zhang, Amr Ahmed, Jie Yang, Vanja Josifovski, Alexander J. Smola

Annotating Needles in the Haystack without Looking: Product Information Extraction from Emails

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The Effectiveness of Marketing Strategies in Social Media: Evidence from Promotional Events

Panagiotis Adamopoulos, Vilma Todri

The Effectiveness of Marketing Strategies in Social Media: Evidence from Promotional Events

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Inferring Networks of Substitutable and Complementary Products

Julian J. McAuley, Rahul Pandey, Jure Leskovec

Inferring Networks of Substitutable and Complementary Products

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Set Cover at Web Scale

Stergios Stergiou, Kostas Tsioutsiouliklis

Set Cover at Web Scale

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Using Local Spectral Methods to Robustify Graph-Based Learning Algorithms

David F. Gleich, Michael W. Mahoney

Using Local Spectral Methods to Robustify Graph-Based Learning Algorithms

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Adaptive Message Update for Fast Affinity Propagation

Yasuhiro Fujiwara, Makoto Nakatsuji, Hiroaki Shiokawa, Yasutoshi Ida, Machiko Toyoda

Adaptive Message Update for Fast Affinity Propagation

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Machine Learning and Causal Inference for Policy Evaluation

Susan Athey

Machine Learning and Causal Inference for Policy Evaluation

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Exploiting Data Mining for Authenticity Assessment and Protection of High-Quality Italian Wines from Piedmont

Marco Arlorio, Jean Daniel Coïsson, Giorgio Leonardi, Monica Locatelli, Luigi Portinale

Exploiting Data Mining for Authenticity Assessment and Protection of High-Quality Italian Wines from Piedmont

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A Collective Bayesian Poisson Factorization Model for Cold-start Local Event Recommendation

Wei Zhang, Jianyong Wang

A Collective Bayesian Poisson Factorization Model for Cold-start Local Event Recommendation

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Online Outlier Exploration Over Large Datasets

Lei Cao, Mingrui Wei, Di Yang, Elke A. Rundensteiner

Online Outlier Exploration Over Large Datasets

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Social Media Anomaly Detection: Challenges and Solutions

Yan Liu, Sanjay Chawla

Social Media Anomaly Detection: Challenges and Solutions

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Estimating Local Intrinsic Dimensionality

Laurent Amsaleg, Oussama Chelly, Teddy Furon, Stéphane Girard, Michael E. Houle, Ken-ichi Kawarabayashi, Michael Nett

Estimating Local Intrinsic Dimensionality

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Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts

Aaron Schein, John William Paisley, David M. Blei, Hanna M. Wallach

Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts

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Visual Search at Pinterest

Yushi Jing, David C. Liu, Dmitry Kislyuk, Andrew Zhai, Jiajing Xu, Jeff Donahue, Sarah Tavel

Visual Search at Pinterest

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Scaling Machine Learning and Statistics for Web Applications

Deepak Agarwal

Scaling Machine Learning and Statistics for Web Applications

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Probabilistic Community and Role Model for Social Networks

Yu Han, Jie Tang

Probabilistic Community and Role Model for Social Networks

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The Child is Father of the Man: Foresee the Success at the Early Stage

Liangyue Li, Hanghang Tong

The Child is Father of the Man: Foresee the Success at the Early Stage

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Subspace Clustering Using Log-determinant Rank Approximation

Chong Peng, Zhao Kang, Huiqing Li, Qiang Cheng

Subspace Clustering Using Log-determinant Rank Approximation

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Should You Trust Your Money to a Robot?

Vasant Dhar

Should You Trust Your Money to a Robot?

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0-Bit Consistent Weighted Sampling

Ping Li

0-Bit Consistent Weighted Sampling

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VEWS: A Wikipedia Vandal Early Warning System

Srijan Kumar, Francesca Spezzano, V. S. Subrahmanian

VEWS: A Wikipedia Vandal Early Warning System

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Multi-View Incident Ticket Clustering for Optimal Ticket Dispatching

Mirela Madalina Botezatu, Jasmina Bogojeska, Ioana Giurgiu, Hagen Völzer, Dorothea Wiesmann

Multi-View Incident Ticket Clustering for Optimal Ticket Dispatching

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Early Prediction of Cardiac Arrest (Code Blue) using Electronic Medical Records

Sriram Somanchi, Samrachana Adhikari, Allen Lin, Elena Eneva, Rayid Ghani

Early Prediction of Cardiac Arrest (Code Blue) using Electronic Medical Records

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Virus Propagation in Multiple Profile Networks

Angeliki Rapti, Spyros Sioutas, Kostas Tsichlas, Giannis Tzimas

Virus Propagation in Multiple Profile Networks

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Data Driven Science: SIGKDD Panel

Katharina Morik, Hugh Durrant-Whyte, Gary Hill, Dietmar Müller, Tanya Y. Berger-Wolf

Data Driven Science: SIGKDD Panel

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Temporal Phenotyping from Longitudinal Electronic Health Records: A Graph Based Framework

Chuanren Liu, Fei Wang, Jianying Hu, Hui Xiong

Temporal Phenotyping from Longitudinal Electronic Health Records: A Graph Based Framework

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Proof Protocol for a Machine Learning Technique Making Longitudinal Predictions in Dynamic Contexts

Kevin B. Pratt

Proof Protocol for a Machine Learning Technique Making Longitudinal Predictions in Dynamic Contexts

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Influence at Scale: Distributed Computation of Complex Contagion in Networks

Brendan Lucier, Joel Oren, Yaron Singer

Influence at Scale: Distributed Computation of Complex Contagion in Networks

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Collaborative Deep Learning for Recommender Systems

Hao Wang, Naiyan Wang, Dit-Yan Yeung

Collaborative Deep Learning for Recommender Systems

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COSNET: Connecting Heterogeneous Social Networks with Local and Global Consistency

Yutao Zhang, Jie Tang, Zhilin Yang, Jian Pei, Philip S. Yu

COSNET: Connecting Heterogeneous Social Networks with Local and Global Consistency

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Probabilistic Graphical Models of Dyslexia

Yair Lakretz, Gal Chechik, Naama Friedmann, Michal Rosen-Zvi

Probabilistic Graphical Models of Dyslexia

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Discovering Collective Narratives of Theme Parks from Large Collections of Visitors' Photo Streams

Gunhee Kim, Leonid Sigal

Discovering Collective Narratives of Theme Parks from Large Collections of Visitors' Photo Streams

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Structural Graphical Lasso for Learning Mouse Brain Connectivity

Sen Yang, Qian Sun, Shuiwang Ji, Peter Wonka, Ian Davidson, Jieping Ye

Structural Graphical Lasso for Learning Mouse Brain Connectivity

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Statistical Arbitrage Mining for Display Advertising

Weinan Zhang, Jun Wang

Statistical Arbitrage Mining for Display Advertising

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TimeCrunch: Interpretable Dynamic Graph Summarization

Neil Shah, Danai Koutra, Tianmin Zou, Brian Gallagher, Christos Faloutsos

TimeCrunch: Interpretable Dynamic Graph Summarization

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Modeling Truth Existence in Truth Discovery

Shi Zhi, Bo Zhao, Wenzhu Tong, Jing Gao, Dian Yu, Heng Ji, Jiawei Han

Modeling Truth Existence in Truth Discovery

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Query Workloads for Data Series Indexes

Kostas Zoumpatianos, Yin Lou, Themis Palpanas, Johannes Gehrke

Query Workloads for Data Series Indexes

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Data Science at Visa

Waqar Hasan, Min Wang

Data Science at Visa

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Diffusion in Social and Information Networks: Research Problems, Probabilistic Models and Machine Learning Methods

Manuel Gomez-Rodriguez, Le Song

Diffusion in Social and Information Networks: Research Problems, Probabilistic Models and Machine Learning Methods

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Towards Decision Support and Goal Achievement: Identifying Action-Outcome Relationships From Social Media

Emre KicKiman, Matthew Richardson

Towards Decision Support and Goal Achievement: Identifying Action-Outcome Relationships From Social Media

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Scalable Machine Learning Approaches for Neighborhood Classification Using Very High Resolution Remote Sensing Imagery

Manu Sethi, Yupeng Yan, Anand Rangarajan, Ranga Raju Vatsavai, Sanjay Ranka

Scalable Machine Learning Approaches for Neighborhood Classification Using Very High Resolution Remote Sensing Imagery

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Client Clustering for Hiring Modeling in Work Marketplaces

Vasilis Verroios, Panagiotis Papadimitriou, Ramesh Johari, Hector Garcia-Molina

Client Clustering for Hiring Modeling in Work Marketplaces

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Debiasing Crowdsourced Batches

Honglei Zhuang, Aditya G. Parameswaran, Dan Roth, Jiawei Han

Debiasing Crowdsourced Batches

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Optimal Action Extraction for Random Forests and Boosted Trees

Zhicheng Cui, Wenlin Chen, Yujie He, Yixin Chen

Optimal Action Extraction for Random Forests and Boosted Trees

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Dynamic Poisson Autoregression for Influenza-Like-Illness Case Count Prediction

Zheng Wang, Prithwish Chakraborty, Sumiko R. Mekaru, John S. Brownstein, Jieping Ye, Naren Ramakrishnan

Dynamic Poisson Autoregression for Influenza-Like-Illness Case Count Prediction

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Discovering Valuable items from Massive Data

Hastagiri P. Vanchinathan, Andreas Marfurt, Charles-Antoine Robelin, Donald Kossmann, Andreas Krause

Discovering Valuable items from Massive Data

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Measuring Causal Impact of Online Actions via Natural Experiments: Application to Display Advertising

Daniel N. Hill, Robert Moakler, Alan E. Hubbard, Vadim Tsemekhman, Foster J. Provost, Kiril Tsemekhman

Measuring Causal Impact of Online Actions via Natural Experiments: Application to Display Advertising

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Matrix Completion with Queries

Natali Ruchansky, Mark Crovella, Evimaria Terzi

Matrix Completion with Queries

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Effective Audience Extension in Online Advertising

Jianqiang Shen, Sahin Cem Geyik, Ali Dasdan

Effective Audience Extension in Online Advertising

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Co-Clustering based Dual Prediction for Cargo Pricing Optimization

Yada Zhu, Hongxia Yang, Jingrui He

Co-Clustering based Dual Prediction for Cargo Pricing Optimization

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Data-Driven Product Innovation

Xin Fu, Hernán Asorey

Data-Driven Product Innovation

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Personalizing LinkedIn Feed

Deepak Agarwal, Bee-Chung Chen, Qi He, Zhenhao Hua, Guy Lebanon, Yiming Ma, Pannagadatta Shivaswamy, Hsiao-Ping Tseng, Jaewon Yang, Liang Zhang

Personalizing LinkedIn Feed

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Distributed Personalization

Xu Miao, Chun-Te Chu, Lijun Tang, Yitong Zhou, Joel Young, Anmol Bhasin

Distributed Personalization

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On Estimating the Swapping Rate for Categorical Data

Daniel Kifer

On Estimating the Swapping Rate for Categorical Data

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Efficient Online Evaluation of Big Data Stream Classifiers

Albert Bifet, Gianmarco De Francisci Morales, Jesse Read, Geoff Holmes, Bernhard Pfahringer

Efficient Online Evaluation of Big Data Stream Classifiers

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Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks

Chenguang Wang, Yangqiu Song, Ahmed El-Kishky, Dan Roth, Ming Zhang, Jiawei Han

Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks

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Learning a Hierarchical Monitoring System for Detecting and Diagnosing Service Issues

Vinod Nair, Ameya Raul, Shwetabh Khanduja, Vikas Bahirwani, Sundararajan Sellamanickam, S. Sathiya Keerthi, Steve Herbert, Sudheer Dhulipalla

Learning a Hierarchical Monitoring System for Detecting and Diagnosing Service Issues

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Utilizing Text Mining on Online Medical Forums to Predict Label Change due to Adverse Drug Reactions

Ronen Feldman, Oded Netzer, Aviv Peretz, Binyamin Rosenfeld

Utilizing Text Mining on Online Medical Forums to Predict Label Change due to Adverse Drug Reactions

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Deep Computational Phenotyping

Zhengping Che, David C. Kale, Wenzhe Li, Mohammad Taha Bahadori, Yan Liu

Deep Computational Phenotyping

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Regularity and Conformity: Location Prediction Using Heterogeneous Mobility Data

Yingzi Wang, Nicholas Jing Yuan, Defu Lian, Linli Xu, Xing Xie, Enhong Chen, Yong Rui

Regularity and Conformity: Location Prediction Using Heterogeneous Mobility Data

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Warm Start for Parameter Selection of Linear Classifiers

Bo-Yu Chu, Chia-Hua Ho, Cheng-Hao Tsai, Chieh-Yen Lin, Chih-Jen Lin

Warm Start for Parameter Selection of Linear Classifiers

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Non-exhaustive, Overlapping Clustering via Low-Rank Semidefinite Programming

Yangyang Hou, Joyce Jiyoung Whang, David F. Gleich, Inderjit S. Dhillon

Non-exhaustive, Overlapping Clustering via Low-Rank Semidefinite Programming

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Quick Sensitivity Analysis for Incremental Data Modification and Its Application to Leave-one-out CV in Linear Classification Problems

Shota Okumura, Yoshiki Suzuki, Ichiro Takeuchi

Quick Sensitivity Analysis for Incremental Data Modification and Its Application to Leave-one-out CV in Linear Classification Problems

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Building Discriminative User Profiles for Large-scale Content Recommendation

Erheng Zhong, Nathan Liu, Yue Shi, Suju Rajan

Building Discriminative User Profiles for Large-scale Content Recommendation

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Differentially Private High-Dimensional Data Publication via Sampling-Based Inference

Rui Chen, Qian Xiao, Yu Zhang, Jianliang Xu

Differentially Private High-Dimensional Data Publication via Sampling-Based Inference

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Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC

Sungjin Ahn, Anoop Korattikara, Nathan Liu, Suju Rajan, Max Welling

Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC

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ALOJA-ML: A Framework for Automating Characterization and Knowledge Discovery in Hadoop Deployments

Josep Lluis Berral, Nicolás Poggi, David Carrera, Aaron Call, Rob Reinauer, Daron Green

ALOJA-ML: A Framework for Automating Characterization and Knowledge Discovery in Hadoop Deployments

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MOOCS: What Have We Learned?

Daphne Koller

MOOCS: What Have We Learned?

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A Decision Tree Framework for Spatiotemporal Sequence Prediction

Taehwan Kim, Yisong Yue, Sarah L. Taylor, Iain A. Matthews

A Decision Tree Framework for Spatiotemporal Sequence Prediction

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Predicting Future Scientific Discoveries Based on a Networked Analysis of the Past Literature

Meenakshi Nagarajan, Angela D. Wilkins, Benjamin J. Bachman, Ilya B. Novikov, Shenghua Bao, Peter J. Haas, María E. Terrón-Díaz, Sumit Bhatia, Anbu K. Adikesavan, Jacques J. Labrie, Sam Regenbogen, Christie M. Buchovecky, Curtis R. Pickering, Linda Kato, Andreas Martin Lisewski, Ana Lelescu, Houyin Zhang, Stephen Boyer, Griff Weber, Ying Chen, Lawrence A. Donehower, W. Scott Spangler, Olivier Lichtarge

Predicting Future Scientific Discoveries Based on a Networked Analysis of the Past Literature

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Hadoop's Impact on the Future of Data Management

Amr Awadallah

Hadoop's Impact on the Future of Data Management

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Why It Happened: Identifying and Modeling the Reasons of the Happening of Social Events

Yu Rong, Hong Cheng, Zhiyu Mo

Why It Happened: Identifying and Modeling the Reasons of the Happening of Social Events

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Tornado Forecasting with Multiple Markov Boundaries

Kui Yu, Dawei Wang, Wei Ding, Jian Pei, David L. Small, Shafiqul Islam, Xindong Wu

Tornado Forecasting with Multiple Markov Boundaries

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More Constraints, Smaller Coresets: Constrained Matrix Approximation of Sparse Big Data

Dan Feldman, Tamir Tassa

More Constraints, Smaller Coresets: Constrained Matrix Approximation of Sparse Big Data

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Learning Tree Structure in Multi-Task Learning

Lei Han, Yu Zhang

Learning Tree Structure in Multi-Task Learning

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On the Discovery of Evolving Truth

Yaliang Li, Qi Li, Jing Gao, Lu Su, Bo Zhao, Wei Fan, Jiawei Han

On the Discovery of Evolving Truth

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Towards Interactive Construction of Topical Hierarchy: A Recursive Tensor Decomposition Approach

Chi Wang, Xueqing Liu, Yanglei Song, Jiawei Han

Towards Interactive Construction of Topical Hierarchy: A Recursive Tensor Decomposition Approach

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User Conditional Hashtag Prediction for Images

Emily Denton, Jason Weston, Manohar Paluri, Lubomir D. Bourdev, Rob Fergus

User Conditional Hashtag Prediction for Images

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Reconstructing Textual Documents from n-grams

Matthias Gallé, Matías Tealdi

Reconstructing Textual Documents from n-grams

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Predictive Modeling for Public Health: Preventing Childhood Lead Poisoning

Eric Potash, Joe Brew, Alexander Loewi, Subhabrata Majumdar, Andrew Reece, Joe Walsh, Eric Rozier, Emile Jorgenson, Raed Mansour, Rayid Ghani

Predictive Modeling for Public Health: Preventing Childhood Lead Poisoning

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Online Controlled Experiments: Lessons from Running A/B/n Tests for 12 Years

Ron Kohavi

Online Controlled Experiments: Lessons from Running A/B/n Tests for 12 Years

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Forecasting Fine-Grained Air Quality Based on Big Data

Yu Zheng, Xiuwen Yi, Ming Li, Ruiyuan Li, Zhangqing Shan, Eric Chang, Tianrui Li

Forecasting Fine-Grained Air Quality Based on Big Data

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Click-through Prediction for Advertising in Twitter Timeline

Cheng Li, Yue Lu, Qiaozhu Mei, Dong Wang, Sandeep Pandey

Click-through Prediction for Advertising in Twitter Timeline

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User Modeling in Telecommunications and Internet Industry

Qiang Yang

User Modeling in Telecommunications and Internet Industry

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Algorithmic Cartography: Placing Points of Interest and Ads on Maps

Mohammad Mahdian, Okke Schrijvers, Sergei Vassilvitskii

Algorithmic Cartography: Placing Points of Interest and Ads on Maps

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Generic and Scalable Framework for Automated Time-series Anomaly Detection

Nikolay Laptev, Saeed Amizadeh, Ian Flint

Generic and Scalable Framework for Automated Time-series Anomaly Detection

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L∞ Error and Bandwidth Selection for Kernel Density Estimates of Large Data

Yan Zheng, Jeff M. Phillips

L∞ Error and Bandwidth Selection for Kernel Density Estimates of Large Data

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Medical Mining: KDD 2015 Tutorial

Myra Spiliopoulou, Pedro Pereira Rodrigues, Ernestina Menasalvas Ruiz

Medical Mining: KDD 2015 Tutorial

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FaitCrowd: Fine Grained Truth Discovery for Crowdsourced Data Aggregation

Fenglong Ma, Yaliang Li, Qi Li, Minghui Qiu, Jing Gao, Shi Zhi, Lu Su, Bo Zhao, Heng Ji, Jiawei Han

FaitCrowd: Fine Grained Truth Discovery for Crowdsourced Data Aggregation

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Efficient Algorithms for Public-Private Social Networks

Flavio Chierichetti, Alessandro Epasto, Ravi Kumar, Silvio Lattanzi, Vahab S. Mirrokni

Efficient Algorithms for Public-Private Social Networks

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Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission

Rich Caruana, Yin Lou, Johannes Gehrke, Paul Koch, Marc Sturm, Noemie Elhadad

Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission

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Discovering and Exploiting Deterministic Label Relationships in Multi-Label Learning

Christina Papagiannopoulou, Grigorios Tsoumakas, Ioannis Tsamardinos

Discovering and Exploiting Deterministic Label Relationships in Multi-Label Learning

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Interpreting Advertiser Intent in Sponsored Search

Bhanu Chandra Vattikonda, Santhosh Kodipaka, Hongyan Zhou, Vacha Dave, Saikat Guha, Alex C. Snoeren

Interpreting Advertiser Intent in Sponsored Search

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Powering Real-time Decision Engines in Finance and Healthcare using Open Source Software

Bassel Ojjeh

Powering Real-time Decision Engines in Finance and Healthcare using Open Source Software

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An Evaluation of Parallel Eccentricity Estimation Algorithms on Undirected Real-World Graphs

Julian Shun

An Evaluation of Parallel Eccentricity Estimation Algorithms on Undirected Real-World Graphs

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Beyond Triangles: A Distributed Framework for Estimating 3-profiles of Large Graphs

Ethan R. Elenberg, Karthikeyan Shanmugam, Michael Borokhovich, Alexandros G. Dimakis

Beyond Triangles: A Distributed Framework for Estimating 3-profiles of Large Graphs

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Heterogeneous Network Embedding via Deep Architectures

Shiyu Chang, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang

Heterogeneous Network Embedding via Deep Architectures

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VC-Dimension and Rademacher Averages: From Statistical Learning Theory to Sampling Algorithms

Matteo Riondato, Eli Upfal

VC-Dimension and Rademacher Averages: From Statistical Learning Theory to Sampling Algorithms

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Voltage Correlations in Smart Meter Data

Rajendu Mitra, Ramachandra Kota, Sambaran Bandyopadhyay, Vijay Arya, Brian Sullivan, Richard Mueller, Heather Storey, Gerard Labut

Voltage Correlations in Smart Meter Data

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Unified and Contrasting Cuts in Multiple Graphs: Application to Medical Imaging Segmentation

Chia-Tung Kuo, Xiang Wang, Peter B. Walker, Owen T. Carmichael, Jieping Ye, Ian Davidson

Unified and Contrasting Cuts in Multiple Graphs: Application to Medical Imaging Segmentation

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Maximum Likelihood Postprocessing for Differential Privacy under Consistency Constraints

Jaewoo Lee, Yue Wang, Daniel Kifer

Maximum Likelihood Postprocessing for Differential Privacy under Consistency Constraints

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Mining Administrative Data to Spur Urban Revitalization

Ben Green, Alejandra Caro, Matthew Conway, Robert Manduca, Tom Plagge, Abby Miller

Mining Administrative Data to Spur Urban Revitalization

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Real-Time Top-R Topic Detection on Twitter with Topic Hijack Filtering

Kohei Hayashi, Takanori Maehara, Masashi Toyoda, Ken-ichi Kawarabayashi

Real-Time Top-R Topic Detection on Twitter with Topic Hijack Filtering

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FrauDetector: A Graph-Mining-based Framework for Fraudulent Phone Call Detection

Vincent S. Tseng, Jia-Ching Ying, Che-Wei Huang, Yimin Kao, Kuan-Ta Chen

FrauDetector: A Graph-Mining-based Framework for Fraudulent Phone Call Detection

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Dynamic Topic Modeling for Monitoring Market Competition from Online Text and Image Data

Hao Zhang, Gunhee Kim, Eric P. Xing

Dynamic Topic Modeling for Monitoring Market Competition from Online Text and Image Data

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Spoken English Grading: Machine Learning with Crowd Intelligence

Vinay Shashidhar, Nishant Pandey, Varun Aggarwal

Spoken English Grading: Machine Learning with Crowd Intelligence

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Smart Pacing for Effective Online Ad Campaign Optimization

Jian Xu, Kuang-chih Lee, Wentong Li, Hang Qi, Quan Lu

Smart Pacing for Effective Online Ad Campaign Optimization

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