ACM Knowledge Discovery and Data Mining, KDD 2016


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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Optimal Reserve Prices in Upstream Auctions: Empirical Application on Online Video Advertising

Miguel Angel Alcobendas Lisbona, Sheide Chammas, Kuang-chih Lee

Optimal Reserve Prices in Upstream Auctions: Empirical Application on Online Video Advertising

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Causal Clustering for 1-Factor Measurement Models

Erich Kummerfeld, Joseph Ramsey

Causal Clustering for 1-Factor Measurement Models

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Scalable Partial Least Squares Regression on Grammar-Compressed Data Matrices

Yasuo Tabei, Hiroto Saigo, Yoshihiro Yamanishi, Simon J. Puglisi

Scalable Partial Least Squares Regression on Grammar-Compressed Data Matrices

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Deploying Analytics with the Portable Format for Analytics (PFA)

Jim Pivarski, Collin Bennett, Robert L. Grossman

Deploying Analytics with the Portable Format for Analytics (PFA)

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Topic Modeling of Short Texts: A Pseudo-Document View

Yuan Zuo, Junjie Wu, Hui Zhang, Hao Lin, Fei Wang, Ke Xu, Hui Xiong

Topic Modeling of Short Texts: A Pseudo-Document View

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Dynamics of Large Multi-View Social Networks: Synergy, Cannibalization and Cross-View Interplay

Yu Shi, Myunghwan Kim, Shaunak Chatterjee, Mitul Tiwari, Souvik Ghosh, Rómer Rosales

Dynamics of Large Multi-View Social Networks: Synergy, Cannibalization and Cross-View Interplay

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Bid-aware Gradient Descent for Unbiased Learning with Censored Data in Display Advertising

Weinan Zhang, Tianxiong Zhou, Jun Wang, Jian Xu

Bid-aware Gradient Descent for Unbiased Learning with Censored Data in Display Advertising

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City-Scale Map Creation and Updating using GPS Collections

Chen Chen, Cewu Lu, Qixing Huang, Qiang Yang, Dimitrios Gunopulos, Leonidas J. Guibas

City-Scale Map Creation and Updating using GPS Collections

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Streaming-LDA: A Copula-based Approach to Modeling Topic Dependencies in Document Streams

Hesam Amoualian, Marianne Clausel, Éric Gaussier, Massih-Reza Amini

Streaming-LDA: A Copula-based Approach to Modeling Topic Dependencies in Document Streams

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Lifelong Machine Learning and Computer Reading the Web

Zhiyuan Chen, Estevam R. Hruschka Jr., Bing Liu

Lifelong Machine Learning and Computer Reading the Web

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Kam1n0: MapReduce-based Assembly Clone Search for Reverse Engineering

Steven H. H. Ding, Benjamin C. M. Fung, Philippe Charland

Kam1n0: MapReduce-based Assembly Clone Search for Reverse Engineering

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Understanding Behaviors that Lead to Purchasing: A Case Study of Pinterest

Caroline Lo, Dan Frankowski, Jure Leskovec

Understanding Behaviors that Lead to Purchasing: A Case Study of Pinterest

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Scalable Data Analytics Using R: Single Machines to Hadoop Spark Clusters

John-Mark Agosta, Debraj GuhaThakurta, Robert Horton, Mario Inchiosa, Srini Kumar, Mengyue Zhao

Scalable Data Analytics Using R: Single Machines to Hadoop Spark Clusters

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FUSE: Full Spectral Clustering

Wei Ye, Sebastian Goebl, Claudia Plant, Christian Böhm

FUSE: Full Spectral Clustering

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CaSMoS: A Framework for Learning Candidate Selection Models over Structured Queries and Documents

Fedor Borisyuk, Krishnaram Kenthapadi, David Stein, Bo Zhao

CaSMoS: A Framework for Learning Candidate Selection Models over Structured Queries and Documents

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Robust Influence Maximization

Wei Chen, Tian Lin, Zihan Tan, Mingfei Zhao, Xuren Zhou

Robust Influence Maximization

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Data-driven Automatic Treatment Regimen Development and Recommendation

Leilei Sun, Chuanren Liu, Chonghui Guo, Hui Xiong, Yanming Xie

Data-driven Automatic Treatment Regimen Development and Recommendation

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Minimizing Legal Exposure of High-Tech Companies through Collaborative Filtering Methods

Bo Jin, Chao Che, Kuifei Yu, Yue Qu, Li Guo, Cuili Yao, Ruiyun Yu, Qiang Zhang

Minimizing Legal Exposure of High-Tech Companies through Collaborative Filtering Methods

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Mining Subgroups with Exceptional Transition Behavior

Florian Lemmerich, Martin Becker, Philipp Singer, Denis Helic, Andreas Hotho, Markus Strohmaier

Mining Subgroups with Exceptional Transition Behavior

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Deep Visual-Semantic Hashing for Cross-Modal Retrieval

Yue Cao, Mingsheng Long, Jianmin Wang, Qiang Yang, Philip S. Yu

Deep Visual-Semantic Hashing for Cross-Modal Retrieval

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Accelerating Online CP Decompositions for Higher Order Tensors

Shuo Zhou, Nguyen Xuan Vinh, James Bailey, Yunzhe Jia, Ian Davidson

Accelerating Online CP Decompositions for Higher Order Tensors

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An Engagement-Based Customer Lifetime Value System for E-commerce

Ali Vanderveld, Addhyan Pandey, Angela Han, Rajesh Parekh

An Engagement-Based Customer Lifetime Value System for E-commerce

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Identifying Earmarks in Congressional Bills

Ellery Wulczyn, Madian Khabsa, Vrushank Vora, Matthew Heston, Joe Walsh, Christopher Berry, Rayid Ghani

Identifying Earmarks in Congressional Bills

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Point-of-Interest Recommendations: Learning Potential Check-ins from Friends

Huayu Li, Yong Ge, Richang Hong, Hengshu Zhu

Point-of-Interest Recommendations: Learning Potential Check-ins from Friends

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Reconstructing an Epidemic Over Time

Polina Rozenshtein, Aristides Gionis, B. Aditya Prakash, Jilles Vreeken

Reconstructing an Epidemic Over Time

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Predict Risk of Relapse for Patients with Multiple Stages of Treatment of Depression

Zhi Nie, Pinghua Gong, Jieping Ye

Predict Risk of Relapse for Patients with Multiple Stages of Treatment of Depression

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Lightweight Monitoring of Distributed Streams

Arnon Lazerson, Daniel Keren, Assaf Schuster

Lightweight Monitoring of Distributed Streams

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Efficient Shift-Invariant Dictionary Learning

Guoqing Zheng, Yiming Yang, Jaime G. Carbonell

Efficient Shift-Invariant Dictionary Learning

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Lossless Separation of Web Pages into Layout Code and Data

Adi Omari, Benny Kimelfeld, Eran Yahav, Sharon Shoham

Lossless Separation of Web Pages into Layout Code and Data

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Days on Market: Measuring Liquidity in Real Estate Markets

Hengshu Zhu, Hui Xiong, Fangshuang Tang, Qi Liu, Yong Ge, Enhong Chen, Yanjie Fu

Days on Market: Measuring Liquidity in Real Estate Markets

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Robust Influence Maximization

Xinran He, David Kempe

Robust Influence Maximization

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A Truth Discovery Approach with Theoretical Guarantee

Houping Xiao, Jing Gao, Zhaoran Wang, Shiyu Wang, Lu Su, Han Liu

A Truth Discovery Approach with Theoretical Guarantee

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Semi-Markov Switching Vector Autoregressive Model-Based Anomaly Detection in Aviation Systems

Igor Melnyk, Arindam Banerjee, Bryan L. Matthews, Nikunj C. Oza

Semi-Markov Switching Vector Autoregressive Model-Based Anomaly Detection in Aviation Systems

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Online Optimization Methods for the Quantification Problem

Purushottam Kar, Shuai Li, Harikrishna Narasimhan, Sanjay Chawla, Fabrizio Sebastiani

Online Optimization Methods for the Quantification Problem

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Unified Point-of-Interest Recommendation with Temporal Interval Assessment

Yanchi Liu, Chuanren Liu, Bin Liu, Meng Qu, Hui Xiong

Unified Point-of-Interest Recommendation with Temporal Interval Assessment

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Computational Social Science: Exciting Progress and Future Challenges

Duncan Watts

Computational Social Science: Exciting Progress and Future Challenges

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Large-Scale Item Categorization in e-Commerce Using Multiple Recurrent Neural Networks

JungWoo Ha, Hyuna Pyo, Jeonghee Kim

Large-Scale Item Categorization in e-Commerce Using Multiple Recurrent Neural Networks

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Can You Teach the Elephant to Dance? AKA: Culture Eats Data Science for Breakfast

Jonathan D. Becher

Can You Teach the Elephant to Dance? AKA: Culture Eats Data Science for Breakfast

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Lexis: An Optimization Framework for Discovering the Hierarchical Structure of Sequential Data

Payam Siyari, Bistra Dilkina, Constantine Dovrolis

Lexis: An Optimization Framework for Discovering the Hierarchical Structure of Sequential Data

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Text Mining in Clinical Domain: Dealing with Noise

Hoang Nguyen, Jon Patrick

Text Mining in Clinical Domain: Dealing with Noise

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Structural Neighborhood Based Classification of Nodes in a Network

Sharad Nandanwar, M. Narasimha Murty

Structural Neighborhood Based Classification of Nodes in a Network

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Positive-Unlabeled Learning in Streaming Networks

Shiyu Chang, Yang Zhang, Jiliang Tang, Dawei Yin, Yi Chang, Mark A. Hasegawa-Johnson, Thomas S. Huang

Positive-Unlabeled Learning in Streaming Networks

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Business Applications of Predictive Modeling at Scale

Qiang Zhu, Songtao Guo, Paul Ogilvie, Yan Liu

Business Applications of Predictive Modeling at Scale

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Label Noise Reduction in Entity Typing by Heterogeneous Partial-Label Embedding

Xiang Ren, Wenqi He, Meng Qu, Clare R. Voss, Heng Ji, Jiawei Han

Label Noise Reduction in Entity Typing by Heterogeneous Partial-Label Embedding

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Dynamic and Robust Wildfire Risk Prediction System: An Unsupervised Approach

Mahsa Salehi, Laura Irina Rusu, Timothy M. Lynar, Anna Phan

Dynamic and Robust Wildfire Risk Prediction System: An Unsupervised Approach

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Algorithmic Bias: From Discrimination Discovery to Fairness-aware Data Mining

Sara Hajian, Francesco Bonchi, Carlos Castillo

Algorithmic Bias: From Discrimination Discovery to Fairness-aware Data Mining

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A Real Linear and Parallel Multiple Longest Common Subsequences (MLCS) Algorithm

Yanni Li, Hui Li, Tihua Duan, Sheng Wang, Zhi Wang, Yang Cheng

A Real Linear and Parallel Multiple Longest Common Subsequences (MLCS) Algorithm

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Efficient Processing of Network Proximity Queries via Chebyshev Acceleration

Mustafa Coskun, Ananth Grama, Mehmet Koyutürk

Efficient Processing of Network Proximity Queries via Chebyshev Acceleration

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Robust and Effective Metric Learning Using Capped Trace Norm: Metric Learning via Capped Trace Norm

Zhouyuan Huo, Feiping Nie, Heng Huang

Robust and Effective Metric Learning Using Capped Trace Norm: Metric Learning via Capped Trace Norm

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Subjectively Interesting Component Analysis: Data Projections that Contrast with Prior Expectations

Bo Kang, Jefrey Lijffijt, Raúl Santos-Rodriguez, Tijl De Bie

Subjectively Interesting Component Analysis: Data Projections that Contrast with Prior Expectations

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From Truth Discovery to Trustworthy Opinion Discovery: An Uncertainty-Aware Quantitative Modeling Approach

Mengting Wan, Xiangyu Chen, Lance M. Kaplan, Jiawei Han, Jing Gao, Bo Zhao

From Truth Discovery to Trustworthy Opinion Discovery: An Uncertainty-Aware Quantitative Modeling Approach

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Scalable Time-Decaying Adaptive Prediction Algorithm

Yinyan Tan, Zhe Fan, Guilin Li, Fangshan Wang, Zhengbing Li, Shikai Liu, Qiuling Pan, Eric P. Xing, Qirong Ho

Scalable Time-Decaying Adaptive Prediction Algorithm

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People, Computers, and The Hot Mess of Real Data

Joseph M. Hellerstein

People, Computers, and The Hot Mess of Real Data

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Catch Me If You Can: Detecting Pickpocket Suspects from Large-Scale Transit Records

Bowen Du, Chuanren Liu, Wenjun Zhou, Zhenshan Hou, Hui Xiong

Catch Me If You Can: Detecting Pickpocket Suspects from Large-Scale Transit Records

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Robust Large-Scale Machine Learning in the Cloud

Steffen Rendle, Dennis Fetterly, Eugene J. Shekita, Bor-Yiing Su

Robust Large-Scale Machine Learning in the Cloud

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FINAL: Fast Attributed Network Alignment

Si Zhang, Hanghang Tong

FINAL: Fast Attributed Network Alignment

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From Prediction to Action: A Closed-Loop Approach for Data-Guided Network Resource Allocation

Yanan Bao, Huasen Wu, Xin Liu

From Prediction to Action: A Closed-Loop Approach for Data-Guided Network Resource Allocation

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Sampling of Attributed Networks from Hierarchical Generative Models

Pablo Robles-Granda, Sebastián Moreno, Jennifer Neville

Sampling of Attributed Networks from Hierarchical Generative Models

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A Multi-Task Learning Formulation for Survival Analysis

Yan Li, Jie Wang, Jieping Ye, Chandan K. Reddy

A Multi-Task Learning Formulation for Survival Analysis

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Overcoming Key Weaknesses of Distance-based Neighbourhood Methods using a Data Dependent Dissimilarity Measure

Kai Ming Ting, Ye Zhu, Mark James Carman, Yue Zhu, Zhi-Hua Zhou

Overcoming Key Weaknesses of Distance-based Neighbourhood Methods using a Data Dependent Dissimilarity Measure

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Predicting Socio-Economic Indicators using News Events

Sunandan Chakraborty, Ashwin Venkataraman, Srikanth Jagabathula, Lakshminarayanan Subramanian

Predicting Socio-Economic Indicators using News Events

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Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability

Lingfei Wu, Ian En-Hsu Yen, Jie Chen, Rui Yan

Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability

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Asymmetric Transitivity Preserving Graph Embedding

Mingdong Ou, Peng Cui, Jian Pei, Ziwei Zhang, Wenwu Zhu

Asymmetric Transitivity Preserving Graph Embedding

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Profiling Users from Online Social Behaviors with Applications for Tencent Social Ads

Ching Law

Profiling Users from Online Social Behaviors with Applications for Tencent Social Ads

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AnyDBC: An Efficient Anytime Density-based Clustering Algorithm for Very Large Complex Datasets

Son T. Mai, Ira Assent, Martin Storgaard

AnyDBC: An Efficient Anytime Density-based Clustering Algorithm for Very Large Complex Datasets

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Analyzing Volleyball Match Data from the 2014 World Championships Using Machine Learning Techniques

Jan Van Haaren, Horesh Ben Shitrit, Jesse Davis, Pascal Fua

Analyzing Volleyball Match Data from the 2014 World Championships Using Machine Learning Techniques

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Just One More: Modeling Binge Watching Behavior

William Trouleau, Azin Ashkan, Weicong Ding, Brian Eriksson

Just One More: Modeling Binge Watching Behavior

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Meta Structure: Computing Relevance in Large Heterogeneous Information Networks

Zhipeng Huang, Yudian Zheng, Reynold Cheng, Yizhou Sun, Nikos Mamoulis, Xiang Li

Meta Structure: Computing Relevance in Large Heterogeneous Information Networks

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Collaborative Multi-View Denoising

Lei Zhang, Shupeng Wang, Xiaoyu Zhang, Yong Wang, Binbin Li, Dinggang Shen, Shuiwang Ji

Collaborative Multi-View Denoising

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Predictors without Borders: Behavioral Modeling of Product Adoption in Three Developing Countries

Muhammad R. Khan, Joshua E. Blumenstock

Predictors without Borders: Behavioral Modeling of Product Adoption in Three Developing Countries

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Portfolio Selections in P2P Lending: A Multi-Objective Perspective

Hongke Zhao, Qi Liu, Guifeng Wang, Yong Ge, Enhong Chen

Portfolio Selections in P2P Lending: A Multi-Objective Perspective

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Parallel Lasso Screening for Big Data Optimization

Qingyang Li, Shuang Qiu, Shuiwang Ji, Paul M. Thompson, Jieping Ye, Jie Wang

Parallel Lasso Screening for Big Data Optimization

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Crime Rate Inference with Big Data

Hongjian Wang, Daniel Kifer, Corina Graif, Zhenhui Li

Crime Rate Inference with Big Data

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Email Volume Optimization at LinkedIn

Rupesh Gupta, Guanfeng Liang, Hsiao-Ping Tseng, Ravi Kiran Holur Vijay, Xiaoyu Chen, Rómer Rosales

Email Volume Optimization at LinkedIn

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A Non-parametric Approach to Detect Epileptogenic Lesions using Restricted Boltzmann Machines

Yijun Zhao, Bilal Ahmed, Thomas Thesen, Karen E. Blackmon, Jennifer G. Dy, Carla E. Brodley, Ruben Kuzniecky, Orrin Devinsky

A Non-parametric Approach to Detect Epileptogenic Lesions using Restricted Boltzmann Machines

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CNTK: Microsoft's Open-Source Deep-Learning Toolkit

Frank Seide, Amit Agarwal

CNTK: Microsoft's Open-Source Deep-Learning Toolkit

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Structured Doubly Stochastic Matrix for Graph Based Clustering: Structured Doubly Stochastic Matrix

Xiaoqian Wang, Feiping Nie, Heng Huang

Structured Doubly Stochastic Matrix for Graph Based Clustering: Structured Doubly Stochastic Matrix

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Recurrent Marked Temporal Point Processes: Embedding Event History to Vector

Nan Du, Hanjun Dai, Rakshit Trivedi, Utkarsh Upadhyay, Manuel Gomez-Rodriguez, Le Song

Recurrent Marked Temporal Point Processes: Embedding Event History to Vector

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Probabilistic Robust Route Recovery with Spatio-Temporal Dynamics

Hao Wu, Jiangyun Mao, Weiwei Sun, Baihua Zheng, Hanyuan Zhang, Ziyang Chen, Wei Wang

Probabilistic Robust Route Recovery with Spatio-Temporal Dynamics

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Latent Space Model for Road Networks to Predict Time-Varying Traffic

Dingxiong Deng, Cyrus Shahabi, Ugur Demiryurek, Linhong Zhu, Rose Yu, Yan Liu

Latent Space Model for Road Networks to Predict Time-Varying Traffic

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The Evolving Meaning of Information Security

Whitfield Diffie

The Evolving Meaning of Information Security

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Convex Optimization for Linear Query Processing under Approximate Differential Privacy

Ganzhao Yuan, Yin Yang, Zhenjie Zhang, Zhifeng Hao

Convex Optimization for Linear Query Processing under Approximate Differential Privacy

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Come-and-Go Patterns of Group Evolution: A Dynamic Model

Tianyang Zhang, Peng Cui, Christos Faloutsos, Yunfei Lu, Hao Ye, Wenwu Zhu, Shiqiang Yang

Come-and-Go Patterns of Group Evolution: A Dynamic Model

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CompanyDepot: Employer Name Normalization in the Online Recruitment Industry

Qiaoling Liu, Faizan Javed, Matt McNair

CompanyDepot: Employer Name Normalization in the Online Recruitment Industry

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Data-Driven Metric Development for Online Controlled Experiments: Seven Lessons Learned

Alex Deng, Xiaolin Shi

Data-Driven Metric Development for Online Controlled Experiments: Seven Lessons Learned

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CatchTartan: Representing and Summarizing Dynamic Multicontextual Behaviors

Meng Jiang, Christos Faloutsos, Jiawei Han

CatchTartan: Representing and Summarizing Dynamic Multicontextual Behaviors

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Robust Extreme Multi-label Learning

Chang Xu, Dacheng Tao, Chao Xu

Robust Extreme Multi-label Learning

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When Social Influence Meets Item Inference

Hui-Ju Hung, Hong-Han Shuai, De-Nian Yang, Liang-Hao Huang, Wang-Chien Lee, Jian Pei, Ming-Syan Chen

When Social Influence Meets Item Inference

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XGBoost: A Scalable Tree Boosting System

Tianqi Chen, Carlos Guestrin

XGBoost: A Scalable Tree Boosting System

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Communication Efficient Distributed Kernel Principal Component Analysis

Maria-Florina Balcan, Yingyu Liang, Le Song, David P. Woodruff, Bo Xie

Communication Efficient Distributed Kernel Principal Component Analysis

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Online Asymmetric Active Learning with Imbalanced Data

Xiaoxuan Zhang, Tianbao Yang, Padmini Srinivasan

Online Asymmetric Active Learning with Imbalanced Data

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How Machine Learning has Finally Solved Wanamaker's Dilemma

Oliver Downs

How Machine Learning has Finally Solved Wanamaker's Dilemma

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Designing Policy Recommendations to Reduce Home Abandonment in Mexico

Klaus Ackermann, Eduardo Blancas Reyes, Sue He, Thomas Anderson Keller, Paul van der Boor, Romana Khan, Rayid Ghani, José Carlos González

Designing Policy Recommendations to Reduce Home Abandonment in Mexico

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Identifying Decision Makers from Professional Social Networks

Shipeng Yu, Evangelia Christakopoulou, Abhishek Gupta

Identifying Decision Makers from Professional Social Networks

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Online Dual Decomposition for Performance and Delivery-Based Distributed Ad Allocation

Jim C. Huang, Rodolphe Jenatton, Cédric Archambeau

Online Dual Decomposition for Performance and Delivery-Based Distributed Ad Allocation

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Compute Job Memory Recommender System Using Machine Learning

Taraneh Taghavi, Maria Lupetini, Yaron Kretchmer

Compute Job Memory Recommender System Using Machine Learning

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Ranking Causal Anomalies via Temporal and Dynamical Analysis on Vanishing Correlations

Wei Cheng, Kai Zhang, Haifeng Chen, Guofei Jiang, Zhengzhang Chen, Wei Wang

Ranking Causal Anomalies via Temporal and Dynamical Analysis on Vanishing Correlations

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Interpretable Decision Sets: A Joint Framework for Description and Prediction

Himabindu Lakkaraju, Stephen H. Bach, Jure Leskovec

Interpretable Decision Sets: A Joint Framework for Description and Prediction

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ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages

Matteo Riondato, Eli Upfal

ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages

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NetCycle: Collective Evolution Inference in Heterogeneous Information Networks

Yizhou Zhang, Yun Xiong, Xiangnan Kong, Yangyong Zhu

NetCycle: Collective Evolution Inference in Heterogeneous Information Networks

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Graph Wavelets via Sparse Cuts

Arlei Silva, Xuan Hong Dang, Prithwish Basu, Ambuj K. Singh, Ananthram Swami

Graph Wavelets via Sparse Cuts

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Distributing the Stochastic Gradient Sampler for Large-Scale LDA

Yuan Yang, Jianfei Chen, Jun Zhu

Distributing the Stochastic Gradient Sampler for Large-Scale LDA

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Online Context-Aware Recommendation with Time Varying Multi-Armed Bandit

Chunqiu Zeng, Qing Wang, Shekoofeh Mokhtari, Tao Li

Online Context-Aware Recommendation with Time Varying Multi-Armed Bandit

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TRIÈST: Counting Local and Global Triangles in Fully-Dynamic Streams with Fixed Memory Size

Lorenzo De Stefani, Alessandro Epasto, Matteo Riondato, Eli Upfal

TRIÈST: Counting Local and Global Triangles in Fully-Dynamic Streams with Fixed Memory Size

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Graphons and Machine Learning: Modeling and Estimation of Sparse Massive Networks

Jennifer T. Chayes

Graphons and Machine Learning: Modeling and Estimation of Sparse Massive Networks

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Towards Optimal Cardinality Estimation of Unions and Intersections with Sketches

Daniel Ting

Towards Optimal Cardinality Estimation of Unions and Intersections with Sketches

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Gemello: Creating a Detailed Energy Breakdown from Just the Monthly Electricity Bill

Nipun Batra, Amarjeet Singh, Kamin Whitehouse

Gemello: Creating a Detailed Energy Breakdown from Just the Monthly Electricity Bill

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Inferring Network Effects from Observational Data

David T. Arbour, Dan Garant, David D. Jensen

Inferring Network Effects from Observational Data

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Infinite Ensemble for Image Clustering

Hongfu Liu, Ming Shao, Sheng Li, Yun Fu

Infinite Ensemble for Image Clustering

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Efficient Frequent Directions Algorithm for Sparse Matrices

Mina Ghashami, Edo Liberty, Jeff M. Phillips

Efficient Frequent Directions Algorithm for Sparse Matrices

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Structural Deep Network Embedding

Daixin Wang, Peng Cui, Wenwu Zhu

Structural Deep Network Embedding

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The Legislative Influence Detector: Finding Text Reuse in State Legislation

Matthew Burgess, Eugenia Giraudy, Julian Katz-Samuels, Joe Walsh, Derek Willis, Lauren Haynes, Rayid Ghani

The Legislative Influence Detector: Finding Text Reuse in State Legislation

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FASCINATE: Fast Cross-Layer Dependency Inference on Multi-layered Networks

Chen Chen, Hanghang Tong, Lei Xie, Lei Ying, Qing He

FASCINATE: Fast Cross-Layer Dependency Inference on Multi-layered Networks

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MANTRA: A Scalable Approach to Mining Temporally Anomalous Sub-trajectories

Prithu Banerjee, Pranali Yawalkar, Sayan Ranu

MANTRA: A Scalable Approach to Mining Temporally Anomalous Sub-trajectories

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Singapore in Motion: Insights on Public Transport Service Level Through Farecard and Mobile Data Analytics

Hasan Poonawala, Vinay Kolar, Sebastien Blandin, Laura Wynter, Sambit Sahu

Singapore in Motion: Insights on Public Transport Service Level Through Farecard and Mobile Data Analytics

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Keeping it Short and Simple: Summarising Complex Event Sequences with Multivariate Patterns

Roel Bertens, Jilles Vreeken, Arno Siebes

Keeping it Short and Simple: Summarising Complex Event Sequences with Multivariate Patterns

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Batch Model for Batched Timestamps Data Analysis with Application to the SSA Disability Program

Qingqi Yue, Ao Yuan, Xuan Che, Minh Huynh, Chunxiao Zhou

Batch Model for Batched Timestamps Data Analysis with Application to the SSA Disability Program

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Towards Conversational Recommender Systems

Konstantina Christakopoulou, Filip Radlinski, Katja Hofmann

Towards Conversational Recommender Systems

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Detecting Devastating Diseases in Search Logs

John Paparrizos, Ryen W. White, Eric Horvitz

Detecting Devastating Diseases in Search Logs

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GLMix: Generalized Linear Mixed Models For Large-Scale Response Prediction

XianXing Zhang, Yitong Zhou, Yiming Ma, Bee-Chung Chen, Liang Zhang, Deepak Agarwal

GLMix: Generalized Linear Mixed Models For Large-Scale Response Prediction

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Online Feature Selection: A Limited-Memory Substitution Algorithm and Its Asynchronous Parallel Variation

Haichuan Yang, Ryohei Fujimaki, Yukitaka Kusumura, Ji Liu

Online Feature Selection: A Limited-Memory Substitution Algorithm and Its Asynchronous Parallel Variation

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GMove: Group-Level Mobility Modeling Using Geo-Tagged Social Media

Chao Zhang, Keyang Zhang, Quan Yuan, Luming Zhang, Tim Hanratty, Jiawei Han

GMove: Group-Level Mobility Modeling Using Geo-Tagged Social Media

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Regime Shifts in Streams: Real-time Forecasting of Co-evolving Time Sequences

Yasuko Matsubara, Yasushi Sakurai

Regime Shifts in Streams: Real-time Forecasting of Co-evolving Time Sequences

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Big Data Needs Big Dreamers: Lessons from Successful Big Data Investors

Evangelos Simoudis, Mark Gorenberg, Tim Guleri, Matt Ocko, Greg Sands

Big Data Needs Big Dreamers: Lessons from Successful Big Data Investors

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EMBERS at 4 years: Experiences operating an Open Source Indicators Forecasting System

Sathappan Muthiah, Patrick Butler, Rupinder Paul Khandpur, Parang Saraf, Nathan Self, Alla Rozovskaya, Liang Zhao, Jose Cadena, Chang-Tien Lu, Anil Vullikanti, Achla Marathe, Kristen Maria Summers, Graham Katz, Andy Doyle, Jaime Arredondo, Dipak K. Gupta, David Mares, Naren Ramakrishnan

EMBERS at 4 years: Experiences operating an Open Source Indicators Forecasting System

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Beyond Sigmoids: The NetTide Model for Social Network Growth, and Its Applications

Chengxi Zang, Peng Cui, Christos Faloutsos

Beyond Sigmoids: The NetTide Model for Social Network Growth, and Its Applications

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PTE: Enumerating Trillion Triangles On Distributed Systems

Ha-Myung Park, Sung-Hyon Myaeng, U. Kang

PTE: Enumerating Trillion Triangles On Distributed Systems

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Evaluating Mobile Apps with A/B and Quasi A/B Tests

Ya Xu, Nanyu Chen

Evaluating Mobile Apps with A/B and Quasi A/B Tests

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EMBERS AutoGSR: Automated Coding of Civil Unrest Events

Parang Saraf, Naren Ramakrishnan

EMBERS AutoGSR: Automated Coding of Civil Unrest Events

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Large-Scale Machine Learning at Verizon: Theory and Applications

Ashok Srivastava

Large-Scale Machine Learning at Verizon: Theory and Applications

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Diversified Temporal Subgraph Pattern Mining

Yi Yang, Da Yan, Huanhuan Wu, James Cheng, Shuigeng Zhou, John C. S. Lui

Diversified Temporal Subgraph Pattern Mining

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FLASH: Fast Bayesian Optimization for Data Analytic Pipelines

Yuyu Zhang, Mohammad Taha Bahadori, Hang Su, Jimeng Sun

FLASH: Fast Bayesian Optimization for Data Analytic Pipelines

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Ranking Universities Based on Career Outcomes of Graduates

Navneet Kapur, Nikita I. Lytkin, Bee-Chung Chen, Deepak Agarwal, Igor Perisic

Ranking Universities Based on Career Outcomes of Graduates

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Recruitment Market Trend Analysis with Sequential Latent Variable Models

Chen Zhu, Hengshu Zhu, Hui Xiong, Pengliang Ding, Fang Xie

Recruitment Market Trend Analysis with Sequential Latent Variable Models

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How to Get Them a Dream Job?: Entity-Aware Features for Personalized Job Search Ranking

Jia Li, Dhruv Arya, Viet Ha-Thuc, Shakti Sinha

How to Get Them a Dream Job?: Entity-Aware Features for Personalized Job Search Ranking

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Healthcare Data Mining with Matrix Models

Fei Wang, Ping Zhang, Joel Dudley

Healthcare Data Mining with Matrix Models

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Joint Community and Structural Hole Spanner Detection via Harmonic Modularity

Lifang He, Chun-Ta Lu, Jiaqi Ma, Jianping Cao, Linlin Shen, Philip S. Yu

Joint Community and Structural Hole Spanner Detection via Harmonic Modularity

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Improving Survey Aggregation with Sparsely Represented Signals

Tianlin Shi, Forest Agostinelli, Matthew Staib, David P. Wipf, Thomas Moscibroda

Improving Survey Aggregation with Sparsely Represented Signals

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Predicting Disk Replacement towards Reliable Data Centers

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

Predicting Disk Replacement towards Reliable Data Centers

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Domain Adaptation in the Absence of Source Domain Data

Boris Chidlovskii, Stéphane Clinchant, Gabriela Csurka

Domain Adaptation in the Absence of Source Domain Data

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Firebird: Predicting Fire Risk and Prioritizing Fire Inspections in Atlanta

Michael Madaio, Shang-Tse Chen, Oliver L. Haimson, Wenwen Zhang, Xiang Cheng, Matthew Hinds-Aldrich, Duen Horng Chau, Bistra Dilkina

Firebird: Predicting Fire Risk and Prioritizing Fire Inspections in Atlanta

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node2vec: Scalable Feature Learning for Networks

Aditya Grover, Jure Leskovec

node2vec: Scalable Feature Learning for Networks

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Scalable Betweenness Centrality Maximization via Sampling

Ahmad Mahmoody, Charalampos E. Tsourakakis, Eli Upfal

Scalable Betweenness Centrality Maximization via Sampling

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Targeted Topic Modeling for Focused Analysis

Shuai Wang, Zhiyuan Chen, Geli Fei, Bing Liu, Sherry Emery

Targeted Topic Modeling for Focused Analysis

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DopeLearning: A Computational Approach to Rap Lyrics Generation

Eric Malmi, Pyry Takala, Hannu Toivonen, Tapani Raiko, Aristides Gionis

DopeLearning: A Computational Approach to Rap Lyrics Generation

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Partial Label Learning via Feature-Aware Disambiguation

Min-Ling Zhang, Bin-Bin Zhou, Xu-Ying Liu

Partial Label Learning via Feature-Aware Disambiguation

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Approximate Personalized PageRank on Dynamic Graphs

Hongyang Zhang, Peter Lofgren, Ashish Goel

Approximate Personalized PageRank on Dynamic Graphs

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Scalable Pattern Matching over Compressed Graphs via Dedensification

Antonio Maccioni, Daniel J. Abadi

Scalable Pattern Matching over Compressed Graphs via Dedensification

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Rebalancing Bike Sharing Systems: A Multi-source Data Smart Optimization

Junming Liu, Leilei Sun, Weiwei Chen, Hui Xiong

Rebalancing Bike Sharing Systems: A Multi-source Data Smart Optimization

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Accelerated Stochastic Block Coordinate Descent with Optimal Sampling

Aston Zhang, Quanquan Gu

Accelerated Stochastic Block Coordinate Descent with Optimal Sampling

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Bayesian Optimization and Embedded Learning Systems

Jeff Schneider

Bayesian Optimization and Embedded Learning Systems

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Learning to Learn and Compositionality with Deep Recurrent Neural Networks: Learning to Learn and Compositionality

Nando de Freitas

Learning to Learn and Compositionality with Deep Recurrent Neural Networks: Learning to Learn and Compositionality

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Fast Memory-efficient Anomaly Detection in Streaming Heterogeneous Graphs

Emaad A. Manzoor, Sadegh M. Milajerdi, Leman Akoglu

Fast Memory-efficient Anomaly Detection in Streaming Heterogeneous Graphs

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Smart Reply: Automated Response Suggestion for Email

Anjuli Kannan, Karol Kurach, Sujith Ravi, Tobias Kaufmann, Andrew Tomkins, Balint Miklos, Greg Corrado, László Lukács, Marina Ganea, Peter Young, Vivek Ramavajjala

Smart Reply: Automated Response Suggestion for Email

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Accelerating the Race to Autonomous Cars

Danny Shapiro

Accelerating the Race to Autonomous Cars

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Absolute Fused Lasso and Its Application to Genome-Wide Association Studies

Tao Yang, Jun Liu, Pinghua Gong, Ruiwen Zhang, Xiaotong Shen, Jieping Ye

Absolute Fused Lasso and Its Application to Genome-Wide Association Studies

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The Limits of Popularity-Based Recommendations, and the Role of Social Ties

Marco Bressan, Stefano Leucci, Alessandro Panconesi, Prabhakar Raghavan, Erisa Terolli

The Limits of Popularity-Based Recommendations, and the Role of Social Ties

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Developing a Data-Driven Player Ranking in Soccer Using Predictive Model Weights

Joel Brooks, Matthew Kerr, John V. Guttag

Developing a Data-Driven Player Ranking in Soccer Using Predictive Model Weights

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How to Compete Online for News Audience: Modeling Words that Attract Clicks

Joon Hee Kim, Amin Mantrach, Alejandro Jaimes, Alice H. Oh

How to Compete Online for News Audience: Modeling Words that Attract Clicks

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Generalized Hierarchical Sparse Model for Arbitrary-Order Interactive Antigenic Sites Identification in Flu Virus Data

Lei Han, Yu Zhang, Xiu-Feng Wan, Tong Zhang

Generalized Hierarchical Sparse Model for Arbitrary-Order Interactive Antigenic Sites Identification in Flu Virus Data

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Joint Optimization of Multiple Performance Metrics in Online Video Advertising

Sahin Cem Geyik, Sergey Faleev, Jianqiang Shen, Sean O'Donnell, Santanu Kolay

Joint Optimization of Multiple Performance Metrics in Online Video Advertising

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Modeling Precursors for Event Forecasting via Nested Multi-Instance Learning

Yue Ning, Sathappan Muthiah, Huzefa Rangwala, Naren Ramakrishnan

Modeling Precursors for Event Forecasting via Nested Multi-Instance Learning

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Computational Drug Repositioning Using Continuous Self-Controlled Case Series

Zhaobin Kuang, James A. Thomson, Michael Caldwell, Peggy L. Peissig, Ron M. Stewart, David Page

Computational Drug Repositioning Using Continuous Self-Controlled Case Series

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Repeat Buyer Prediction for E-Commerce

Guimei Liu, Tam T. Nguyen, Gang Zhao, Wei Zha, Jianbo Yang, Jianneng Cao, Min Wu, Peilin Zhao, Wei Chen

Repeat Buyer Prediction for E-Commerce

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Images Don't Lie: Transferring Deep Visual Semantic Features to Large-Scale Multimodal Learning to Rank

Corey Lynch, Kamelia Aryafar, Josh Attenberg

Images Don't Lie: Transferring Deep Visual Semantic Features to Large-Scale Multimodal Learning to Rank

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Convolutional Neural Networks for Steady Flow Approximation

Xiaoxiao Guo, Wei Li, Francesco Iorio

Convolutional Neural Networks for Steady Flow Approximation

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A Text Clustering Algorithm Using an Online Clustering Scheme for Initialization

Jianhua Yin, Jianyong Wang

A Text Clustering Algorithm Using an Online Clustering Scheme for Initialization

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Goal-Directed Inductive Matrix Completion

Si Si, Kai-Yang Chiang, Cho-Jui Hsieh, Nikhil Rao, Inderjit S. Dhillon

Goal-Directed Inductive Matrix Completion

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Annealed Sparsity via Adaptive and Dynamic Shrinking

Kai Zhang, Shandian Zhe, Chaoran Cheng, Zhi Wei, Zhengzhang Chen, Haifeng Chen, Guofei Jiang, Yuan Qi, Jieping Ye

Annealed Sparsity via Adaptive and Dynamic Shrinking

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IoT Big Data Stream Mining

Gianmarco De Francisci Morales, Albert Bifet, Latifur Khan, João Gama, Wei Fan

IoT Big Data Stream Mining

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FRAUDAR: Bounding Graph Fraud in the Face of Camouflage

Bryan Hooi, Hyun Ah Song, Alex Beutel, Neil Shah, Kijung Shin, Christos Faloutsos

FRAUDAR: Bounding Graph Fraud in the Face of Camouflage

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Question Independent Grading using Machine Learning: The Case of Computer Program Grading

Gursimran Singh, Shashank Srikant, Varun Aggarwal

Question Independent Grading using Machine Learning: The Case of Computer Program Grading

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Fast Component Pursuit for Large-Scale Inverse Covariance Estimation

Lei Han, Yu Zhang, Tong Zhang

Fast Component Pursuit for Large-Scale Inverse Covariance Estimation

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QUINT: On Query-Specific Optimal Networks

Liangyue Li, Yuan Yao, Jie Tang, Wei Fan, Hanghang Tong

QUINT: On Query-Specific Optimal Networks

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Predicting Matchups and Preferences in Context

Shuo Chen, Thorsten Joachims

Predicting Matchups and Preferences in Context

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Anomaly Detection Using Program Control Flow Graph Mining From Execution Logs

Animesh Nandi, Atri Mandal, Shubham Atreja, Gargi Banerjee Dasgupta, Subhrajit Bhattacharya

Anomaly Detection Using Program Control Flow Graph Mining From Execution Logs

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Burstiness Scale: A Parsimonious Model for Characterizing Random Series of Events

Rodrigo Augusto da Silva Alves, Renato Martins Assunção, Pedro Olmo Stancioli Vaz de Melo

Burstiness Scale: A Parsimonious Model for Characterizing Random Series of Events

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Dynamic Clustering of Streaming Short Documents

Shangsong Liang, Emine Yilmaz, Evangelos Kanoulas

Dynamic Clustering of Streaming Short Documents

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A Multiple Test Correction for Streams and Cascades of Statistical Hypothesis Tests

Geoffrey I. Webb, François Petitjean

A Multiple Test Correction for Streams and Cascades of Statistical Hypothesis Tests

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Boosted Decision Tree Regression Adjustment for Variance Reduction in Online Controlled Experiments

Alexey Poyarkov, Alexey Drutsa, Andrey Khalyavin, Gleb Gusev, Pavel Serdyukov

Boosted Decision Tree Regression Adjustment for Variance Reduction in Online Controlled Experiments

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Mining Reliable Information from Passively and Actively Crowdsourced Data

Jing Gao, Qi Li, Bo Zhao, Wei Fan, Jiawei Han

Mining Reliable Information from Passively and Actively Crowdsourced Data

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Talent Circle Detection in Job Transition Networks

Huang Xu, Zhiwen Yu, Jingyuan Yang, Hui Xiong, Hengshu Zhu

Talent Circle Detection in Job Transition Networks

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Optimally Discriminative Choice Sets in Discrete Choice Models: Application to Data-Driven Test Design

Igor Labutov, Frans Schalekamp, Kelvin Luu, Hod Lipson, Christoph Studer

Optimally Discriminative Choice Sets in Discrete Choice Models: Application to Data-Driven Test Design

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Unbounded Human Learning: Optimal Scheduling for Spaced Repetition

Siddharth Reddy, Igor Labutov, Siddhartha Banerjee, Thorsten Joachims

Unbounded Human Learning: Optimal Scheduling for Spaced Repetition

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Hierarchical Incomplete Multi-source Feature Learning for Spatiotemporal Event Forecasting

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

Hierarchical Incomplete Multi-source Feature Learning for Spatiotemporal Event Forecasting

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Learning Sparse Models at Scale

Ralf Herbrich

Learning Sparse Models at Scale

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User Identity Linkage by Latent User Space Modelling

Xin Mu, Feida Zhu, Ee-Peng Lim, Jing Xiao, Jianzong Wang, Zhi-Hua Zhou

User Identity Linkage by Latent User Space Modelling

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"Why Should I Trust You?": Explaining the Predictions of Any Classifier

Marco Túlio Ribeiro, Sameer Singh, Carlos Guestrin

"Why Should I Trust You?": Explaining the Predictions of Any Classifier

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Audience Expansion for Online Social Network Advertising

Haishan Liu, David Pardoe, Kun Liu, Manoj Thakur, Frank Cao, Chongzhe Li

Audience Expansion for Online Social Network Advertising

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Transfer Knowledge between Cities

Ying Wei, Yu Zheng, Qiang Yang

Transfer Knowledge between Cities

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MAP: Frequency-Based Maximization of Airline Profits based on an Ensemble Forecasting Approach

Bo An, Haipeng Chen, Noseong Park, V. S. Subrahmanian

MAP: Frequency-Based Maximization of Airline Profits based on an Ensemble Forecasting Approach

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Compact and Scalable Graph Neighborhood Sketching

Takuya Akiba, Yosuke Yano

Compact and Scalable Graph Neighborhood Sketching

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Collective Sensemaking via Social Sensors: Extracting, Profiling, Analyzing, and Predicting Real-world Events

Yuheng Hu, Yu-Ru Lin, Jiebo Luo

Collective Sensemaking via Social Sensors: Extracting, Profiling, Analyzing, and Predicting Real-world Events

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Contextual Intent Tracking for Personal Assistants

Yu Sun, Nicholas Jing Yuan, Yingzi Wang, Xing Xie, Kieran McDonald, Rui Zhang

Contextual Intent Tracking for Personal Assistants

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Identifying Police Officers at Risk of Adverse Events

Samuel Carton, Jennifer Helsby, Kenneth Joseph, Ayesha Mahmud, Youngsoo Park, Joe Walsh, Crystal Cody, C. P. T. Estella Patterson, Lauren Haynes, Rayid Ghani

Identifying Police Officers at Risk of Adverse Events

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Aircraft Trajectory Prediction Made Easy with Predictive Analytics

Samet Ayhan, Hanan Samet

Aircraft Trajectory Prediction Made Easy with Predictive Analytics

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The Wisdom of Crowds: Best Practices for Data Prep & Machine Learning Derived from Millions of Data Science Workflows

Ingo Mierswa

The Wisdom of Crowds: Best Practices for Data Prep & Machine Learning Derived from Millions of Data Science Workflows

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Deep Crossing: Web-Scale Modeling without Manually Crafted Combinatorial Features

Ying Shan, T. Ryan Hoens, Jian Jiao, Haijing Wang, Dong Yu, J. C. Mao

Deep Crossing: Web-Scale Modeling without Manually Crafted Combinatorial Features

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Finding Gangs in War from Signed Networks

Lingyang Chu, Zhefeng Wang, Jian Pei, Jiannan Wang, Zijin Zhao, Enhong Chen

Finding Gangs in War from Signed Networks

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Ranking Relevance in Yahoo Search

Dawei Yin, Yuening Hu, Jiliang Tang, Tim Daly Jr., Mianwei Zhou, Hua Ouyang, Jianhui Chen, Changsung Kang, Hongbo Deng, Chikashi Nobata, Jean-Marc Langlois, Yi Chang

Ranking Relevance in Yahoo Search

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Towards Robust and Versatile Causal Discovery for Business Applications

Giorgos Borboudakis, Ioannis Tsamardinos

Towards Robust and Versatile Causal Discovery for Business Applications

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Improving the Sensitivity of Online Controlled Experiments: Case Studies at Netflix

Huizhi Xie, Juliette Aurisset

Improving the Sensitivity of Online Controlled Experiments: Case Studies at Netflix

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Squish: Near-Optimal Compression for Archival of Relational Datasets

Yihan Gao, Aditya G. Parameswaran

Squish: Near-Optimal Compression for Archival of Relational Datasets

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Compressing Convolutional Neural Networks in the Frequency Domain

Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen

Compressing Convolutional Neural Networks in the Frequency Domain

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Scalable Fast Rank-1 Dictionary Learning for fMRI Big Data Analysis

Xiang Li, Milad Makkie, Binbin Lin, Mojtaba Sedigh Fazli, Ian Davidson, Jieping Ye, Tianming Liu, Shannon Quinn

Scalable Fast Rank-1 Dictionary Learning for fMRI Big Data Analysis

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Taxi Driving Behavior Analysis in Latent Vehicle-to-Vehicle Networks: A Social Influence Perspective

Tong Xu, Hengshu Zhu, Xiangyu Zhao, Qi Liu, Hao Zhong, Enhong Chen, Hui Xiong

Taxi Driving Behavior Analysis in Latent Vehicle-to-Vehicle Networks: A Social Influence Perspective

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Parallel Dual Coordinate Descent Method for Large-scale Linear Classification in Multi-core Environments

Wei-Lin Chiang, Mu-Chu Lee, Chih-Jen Lin

Parallel Dual Coordinate Descent Method for Large-scale Linear Classification in Multi-core Environments

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Bayesian Inference of Arrival Rate and Substitution Behavior from Sales Transaction Data with Stockouts

Benjamin Letham, Lydia M. Letham, Cynthia Rudin

Bayesian Inference of Arrival Rate and Substitution Behavior from Sales Transaction Data with Stockouts

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The Million Domain Challenge: Broadcast Email Prioritization by Cross-domain Recommendation

Beidou Wang, Martin Ester, Yikang Liao, Jiajun Bu, Yu Zhu, Ziyu Guan, Deng Cai

The Million Domain Challenge: Broadcast Email Prioritization by Cross-domain Recommendation

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A Subsequence Interleaving Model for Sequential Pattern Mining

Jaroslav M. Fowkes, Charles A. Sutton

A Subsequence Interleaving Model for Sequential Pattern Mining

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A VC View of Investing in ML

Greg Papadopoulos

A VC View of Investing in ML

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Temporal Order-based First-Take-All Hashing for Fast Attention-Deficit-Hyperactive-Disorder Detection

Hao Hu, Joey Velez-Ginorio, Guo-Jun Qi

Temporal Order-based First-Take-All Hashing for Fast Attention-Deficit-Hyperactive-Disorder Detection

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Towards Confidence in the Truth: A Bootstrapping based Truth Discovery Approach

Houping Xiao, Jing Gao, Qi Li, Fenglong Ma, Lu Su, Yunlong Feng, Aidong Zhang

Towards Confidence in the Truth: A Bootstrapping based Truth Discovery Approach

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DeepIntent: Learning Attentions for Online Advertising with Recurrent Neural Networks

Shuangfei Zhai, Keng-hao Chang, Ruofei Zhang, Zhongfei (Mark) Zhang

DeepIntent: Learning Attentions for Online Advertising with Recurrent Neural Networks

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Privacy-preserving Class Ratio Estimation

Arun Shankar Iyer, J. Saketha Nath, Sunita Sarawagi

Privacy-preserving Class Ratio Estimation

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Extracting Optimal Performance from Dynamic Time Warping

Abdullah Mueen, Eamonn J. Keogh

Extracting Optimal Performance from Dynamic Time Warping

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When Recommendation Goes Wrong: Anomalous Link Discovery in Recommendation Networks

Bryan Perozzi, Michael Schueppert, Jack Saalweachter, Mayur Thakur

When Recommendation Goes Wrong: Anomalous Link Discovery in Recommendation Networks

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Safe Pattern Pruning: An Efficient Approach for Predictive Pattern Mining

Kazuya Nakagawa, Shinya Suzumura, Masayuki Karasuyama, Koji Tsuda, Ichiro Takeuchi

Safe Pattern Pruning: An Efficient Approach for Predictive Pattern Mining

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Scalable Learning of Graphical Models

François Petitjean, Geoffrey I. Webb

Scalable Learning of Graphical Models

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Compressing Graphs and Indexes with Recursive Graph Bisection

Laxman Dhulipala, Igor Kabiljo, Brian Karrer, Giuseppe Ottaviano, Sergey Pupyrev, Alon Shalita

Compressing Graphs and Indexes with Recursive Graph Bisection

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An Empirical Study on Recommendation with Multiple Types of Feedback

Liang Tang, Bo Long, Bee-Chung Chen, Deepak Agarwal

An Empirical Study on Recommendation with Multiple Types of Feedback

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Fast Unsupervised Online Drift Detection Using Incremental Kolmogorov-Smirnov Test

Denis Moreira dos Reis, Peter A. Flach, Stan Matwin, Gustavo Batista

Fast Unsupervised Online Drift Detection Using Incremental Kolmogorov-Smirnov Test

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Engagement Capacity and Engaging Team Formation for Reach Maximization of Online Social Media Platforms

Alexander G. Nikolaev, Shounak Gore, Venu Govindaraju

Engagement Capacity and Engaging Team Formation for Reach Maximization of Online Social Media Platforms

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From Online Behaviors to Offline Retailing

Ping Luo, Su Yan, Zhiqiang Liu, Zhiyong Shen, Shengwen Yang, Qing He

From Online Behaviors to Offline Retailing

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Multi-Task Feature Interaction Learning

Kaixiang Lin, Jianpeng Xu, Inci M. Baytas, Shuiwang Ji, Jiayu Zhou

Multi-Task Feature Interaction Learning

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Continuous Experience-aware Language Model

Subhabrata Mukherjee, Stephan Günnemann, Gerhard Weikum

Continuous Experience-aware Language Model

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Leveraging Propagation for Data Mining: Models, Algorithms and Applications

B. Aditya Prakash, Naren Ramakrishnan

Leveraging Propagation for Data Mining: Models, Algorithms and Applications

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Collaborative Knowledge Base Embedding for Recommender Systems

Fuzheng Zhang, Nicholas Jing Yuan, Defu Lian, Xing Xie, Wei-Ying Ma

Collaborative Knowledge Base Embedding for Recommender Systems

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Assessing Human Error Against a Benchmark of Perfection

Ashton Anderson, Jon M. Kleinberg, Sendhil Mullainathan

Assessing Human Error Against a Benchmark of Perfection

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Streaming Analytics

Ashish Gupta, Neera Agarwal

Streaming Analytics

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Smart Broadcasting: Do You Want to be Seen?

Mohammad Reza Karimi, Erfan Tavakoli, Mehrdad Farajtabar, Le Song, Manuel Gomez-Rodriguez

Smart Broadcasting: Do You Want to be Seen?

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Matrix Computations and Optimization in Apache Spark

Reza Bosagh Zadeh, Xiangrui Meng, Alexander Ulanov, Burak Yavuz, Li Pu, Shivaram Venkataraman, Evan R. Sparks, Aaron Staple, Matei Zaharia

Matrix Computations and Optimization in Apache Spark

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Multi-layer Representation Learning for Medical Concepts

Edward Choi, Mohammad Taha Bahadori, Elizabeth Searles, Catherine Coffey, Michael Thompson, James Bost, Javier Tejedor-Sojo, Jimeng Sun

Multi-layer Representation Learning for Medical Concepts

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Extreme Multi-label Loss Functions for Recommendation, Tagging, Ranking & Other Missing Label Applications

Himanshu Jain, Yashoteja Prabhu, Manik Varma

Extreme Multi-label Loss Functions for Recommendation, Tagging, Ranking & Other Missing Label Applications

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Learning Cumulatively to Become More Knowledgeable

Geli Fei, Shuai Wang, Bing Liu

Learning Cumulatively to Become More Knowledgeable

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Skinny-dip: Clustering in a Sea of Noise

Samuel Maurus, Claudia Plant

Skinny-dip: Clustering in a Sea of Noise

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