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)

时间: 2024-10-10 12:05:44

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