ICML历年Best Papers

作者：我爱机器学习
原文链接：ICML历年Best Papers

ICML (Machine Learning)(1999-2016)
2016	Dueling Network Architectures for Deep Reinforcement Learning	Ziyu Wang	Google Inc.
	Pixel Recurrent Neural Networks	Aaron van den Oord	Google DeepMind
	Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling	Christopher De Sa	Stanford
2015	A Nearly-Linear Time Framework for Graph-Structured Sparsity	Chinmay Hegde	Massachusetts Institute of Technology
	Optimal and Adaptive Algorithms for Online Boosting	Alina Beygelzimer	Yahoo! Research
2014	Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis	Jian Tang	Peking University
2013	Vanishing Component Analysis	Roi Livni	The Hebrew University of Jerusalum
	Fast Semidifferential-based Submodular Function Optimization	Rishabh Iyer	University of Washington
2012	Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring	Sungjin Ahn	University of California Irvine
2011	Computational Rationalization: The Inverse Equilibrium Problem	Kevin Waugh	Carnegie Mellon University
2010	Hilbert Space Embeddings of Hidden Markov Models	Le Song	Carnegie Mellon University
2009	Structure preserving embedding	Blake Shaw	Columbia University
2008	SVM Optimization: Inverse Dependence on Training Set Size	Shai Shalev-Shwartz	Toyota Technological Institute at Chicago
2007	Information-theoretic metric learning	Jason V. Davis	University of Texas at Austin
2006	Trading convexity for scalability	Ronan Collobert	NEC Labs America
2005	A support vector method for multivariate performance measures	Thorsten Joachims	Cornell University
1999	Least-Squares Temporal Difference Learning	Justin A. Boyan	NASA Ames Research Center

参考文献：Best Paper Awards in Computer Science (since 1996)