ICML (Machine Learning)(Average MAP score: 0.01)

ICML (Machine Learning) 2011

( MAP score: 0.0 )

• Rank
  1

  Cited by
  67

  The Importance of Encoding Versus Training with Sparse Coding and Vector Quantization

• 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 )

• 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 )

• 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 )

• 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 )

• 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 )

• 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 )

• 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 )

• 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