Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods

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Title:	Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods
Article URLs:	http://papers.nips.cc/paper/6565-learning-supervised-pagerank-with-gradient-based-and-gradient-free-optimization-methods
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Authors:	Lev Bogolubsky	Yandex Moscow State University
	Pavel E. Dvurechensky	Weierstrass Institute Institute for Information Transmission Problems RAS
	Alexander Gasnikov	Institute for Information Transmission Problems RAS Moscow Institute of Physics and Technology
	Gleb Gusev	Yandex Moscow Institute of Physics and Technology
	Yurii E. Nesterov	Center for Operations Research and Econometrics Higher School of Economics
	Andrei M. Raigorodskii	Yandex Moscow State University Moscow Institute of Physics and Technology Buryat State University
	Aleksey Tikhonov	Yandex
	Maksim Zhukovskii	Yandex Moscow Institute of Physics and Technology
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Artifact URLs:	http://papers.nips.cc/paper/6565-learning-supervised-pagerank-with-gradient-based-and-gradient-free-optimization-methods-supplemental.zip
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DBLP Key:	conf/nips/BogolubskyDGGNR16
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Advances in Neural Information Processing Systems, NIPS 2016