Best of Best系列（3）——ICML

Best of Best系列（3）——ICML

ICML (Machine Learning)(Average MAP score: 0.01)
ICML (Machine Learning) 2011 ( MAP score: 0.0 ) TOP
Rank 1 Cited by 67 The Importance of Encoding Versus Training with Sparse Coding and Vector Quantization Adam Coates, Andrew Y. Ng Rank 2 Cited by 34 Parsing Natural Scenes and Natural Language with Recursive Neural Networks Richard Socher, Cliff Chiung-Yu Lin, Andrew Y. Ng, Christopher D. Manning Rank 3 Cited by 30 Learning Recurrent Neural Networks with Hessian-Free Optimization James Martens, Ilya Sutskever BEST PAPER! Rank 71 Cited by 5 Computational Rationalization: The Inverse Equilibrium Problem Kevin Waugh, Brian Ziebart, Drew Bagnell
ICML (Machine Learning) 2010 ( MAP score: 0.0 ) TOP
Rank 1 Cited by 113 Proximal Methods for Sparse Hierarchical Dictionary Learning Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis Bach Rank 2 Cited by 113 Detecting Large-Scale System Problems by Mining Console Logs Wei Xu, Ling Huang, Armando Fox, David Patterson, Michael I. Jordan Rank 3 Cited by 91 Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity Seyoung Kim, Eric P. Xing BEST PAPER! Rank 16 Cited by 35 Hilbert Space Embeddings of Hidden Markov Models Le Song, Sajid M. Siddiqi, Geoffrey J. Gordon, Alexander J. Smola
ICML (Machine Learning) 2009 ( MAP score: 0.0 ) TOP
Rank 1 Cited by 245 Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations Honglak Lee, Roger Grosse, Rajesh Ranganath, Andrew Y. Ng Rank 2 Cited by 215 Online dictionary learning for sparse coding Julien Mairal, Francis Bach, Jean Ponce, Guillermo Sapiro Rank 3 Cited by 184 Group lasso with overlap and graph lasso Laurent Jacob, Guillaume Obozinski, Jean-Philippe Vert BEST PAPER! Rank 39 Cited by 38 Structure preserving embedding Blake Shaw, Tony Jebara
ICML (Machine Learning) 2008 ( MAP score: 0.0 ) TOP
Rank 1 Cited by 225 Efficient projections onto the -ball for learning in high dimensions John Duchi, Shai Shalev-Shwartz, Yoram Singer, Tushar Chandra Rank 2 Cited by 202 A dual coordinate descent method for large-scale linear SVM Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin, S. Sathiya Keerthi, S. Sundararajan Rank 3 Cited by 200 A unified architecture for natural language processing: deep neural networks with multitask learning Ronan Collobert, Jason Weston BEST PAPER! Rank 11 Cited by 96 SVM optimization: inverse dependence on training set size Shai Shalev-Shwartz, Nathan Srebro
ICML (Machine Learning) 2007 ( MAP score: 0.0 ) TOP
Rank 1 Cited by 473 Pegasos: Primal Estimated sub-GrAdient SOlver for SVM Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro Rank 2 Cited by 381 Self-taught learning: transfer learning from unlabeled data Rajat Raina, Alexis Battle, Honglak Lee, Benjamin Packer, Andrew Y. Ng Rank 3 Cited by 367 Learning to rank: from pairwise approach to listwise approach Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, Hang Li BEST PAPER! Rank 4 Cited by 353 Information-theoretic metric learning Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit Sra, Inderjit S. Dhillon
ICML (Machine Learning) 2006 ( MAP score: 0.0 ) TOP
Rank 1 Cited by 462 Dynamic topic models David M. Blei, John D. Lafferty Rank 2 Cited by 438 The relationship between Precision-Recall and ROC curves Jesse Davis, Mark Goadrich Rank 3 Cited by 362 An empirical comparison of supervised learning algorithms Rich Caruana, Alexandru Niculescu-Mizil BEST PAPER! Rank 8 Cited by 139 Trading convexity for scalability Ronan Collobert, Fabian H. Sinz, Jason Weston, Léon Bottou
ICML (Machine Learning) 2005 ( MAP score: 0.11 ) TOP
Rank 1 Cited by 1110 Fast condensed nearest neighbor rule Fabrizio Angiulli Rank 2 Cited by 698 Learning to rank using gradient descent Christopher J. C. Burges, Tal Shaked, Erin Renshaw, Ari Lazier, Matt Deeds, Nicole Hamilton, Gregory N. Hullender BEST PAPER! Rank 3 Cited by 369 A support vector method for multivariate performance measures Thorsten Joachims
ICML (Machine Learning) 1999 ( MAP score: 0.0 ) TOP
Rank 1 Cited by 1634 Transductive Inference for Text Classification using Support Vector Machines Thorsten Joachims Rank 2 Cited by 382 The Alternating Decision Tree Learning Algorithm Yoav Freund, Llew Mason Rank 3 Cited by 323 AdaCost: Misclassification Cost-Sensitive Boosting Wei Fan, Salvatore J. Stolfo, Junxin Zhang, Philip K. Chan BEST PAPER! Rank N/A Cited by N/A Least-Squares Temporal Difference Learning Justin A. Boyan

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原文地址：https://www.cnblogs.com/youth0826/p/3010334.html