Half Transductive Ranking, Bing Bai, Jason Weston, D. Grangier, R. Collobert, C. Cortes, M. Mohri, Artificial Intelligence and Statistics (AISTATS), 2010 (to appear).
Large Scale Online Learning of Image Similarity Through Ranking, Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio, Journal of Machine Learning Research (JMLR) (2010) (to appear).
Parallel Spectral Clustering in Distributed Systems, Wen-Yen Chen, Yangqiu Song, Hongjie Bai, Chih-Jen Lin, Edward Y. Chang, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010.
Random classification noise defeats all convex potential boosters, Philip M. Long, Rocco A. Servedio, Machine Learning, vol. 78 (2010), pp. 287-304.
Towards Understanding Situated Natural Language, Antoine Bordes, Nicolas Usunier, Jason Weston, Artificial Intelligence and Statistics (AISTATS), 2010 (to appear).
Why does Unsupervised Pre-training Help Deep Learning?, Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio, Journal of Machine Learning Research (2010), pp. 625-660.
An Online Algorithm for Large Scale Image Similarity Learning, Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio, Advances in Neural Information Processing Systems, 2009.
Automatic Speech and Speaker Recognition: Large Margin and Kernel Methods, Joseph Keshet, Samy Bengio, 2009.
Baum's algorithm learns intersections of halfspaces with respect to log-concave distributions, Adam R. Klivans, Philip M. Long, Alex K. Tang, RANDOM, 2009.
Boosting with structural sparsity, John Duchi, Yoram Singer, ICML '09: Proceedings of the 26th Annual International Conference on Machine Learning, 2009, pp. 297-304.
Des algorithmes d'apprentissage pour mieux classifier, Corinna Cortes, Patrick Haffner, Mehryar Mohri, Pour la Science, vol. 386 (2009).
Discriminative Keyword Spotting, David Grangier, Joseph Keshet, Samy Bengio, Automatic Speech and Speaker Recognition: Large Margin and Kernel Methods, 2009.
Discriminative Keyword Spotting, Joseph Keshet, David Grangier, Samy Bengio, Speech Communication (2009), pp. 317-329.
Domain Adaptation with Multiple Sources, Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh, Advances in Neural Information Processing Systems (NIPS 2008), 2009.
Domain Adaptation: Learning Bounds and Algorithms, Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh, Proceedings of The 22nd Annual Conference on Learning Theory (COLT 2009).
Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models, Gideon Mann, Ryan McDonald, Mehryar Mohri, Nathan Silberman, Daniel Walker IV, Neural Information Processing Systems (NIPS), 2009.
Ensemble Nystrom Method, Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar, Neural Information Processing Systems (NIPS), 2009.
Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification, Amarnag Subramanya, Jeff Bilmes, NIPS 2009 (2009).
Finding Images and Line Drawings in Document-Scanning Systems, Shumeet Baluja, Michele Covell, Proc. International Conference on Document Analysis and Retrieval, 2009.
Gaussian Margin Machines, Koby Crammer, Mehryar Mohri, Fernando Pereira, Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS 2009), pp. 105-112.
Group Sparse Coding, Samy Bengio, Fernando Pereira, Yoram Singer, Dennis Strelow, Advances in Neural Information Processing Systems, 2009.
Introduction, Samy Bengio, Joseph Keshet, Automatic Speech and Speaker Recognition: Large Margin and Kernel Methods, 2009.
Invited talk: Can learning kernels help performance?, Corinna Cortes, ICML '09: Proceedings of the 26th Annual International Conference on Machine Learning, 2009, pp. 1-1.
Kernel Based Text-Independnent Speaker Verification, Johnny Mariethoz, Yves Grandvalet, Samy Bengio, Automatic Speech and Speaker Recognition: Large Margin and Kernel Methods, 2009.
L2 Regularization for Learning Kernels, Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh, Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence (UAI 2009).
Large Scale Graph Transduction, Amarnag Subramanya, Jeff Bilmes, NIPS 2009 Workshop on Large-Scale Machine Learning: Parallelism and Massive Datasets (2009).
Large Scale Learning to Rank, D. Sculley, NIPS 2009 Workshop on Advances in Ranking.
Large Scale Online Learning of Image Similarity Through Ranking: Extended Abstract, Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio, 4th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA, 2009.
Learning Halfspaces with Malicious Noise, Adam R. Klivans, Philip M. Long, Rocco A. Servedio, JMLR, vol. 10 (2009), pp. 2715-2740.
Learning non-linear combinations of kernels, Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh, Advances in Neural Information Processing Systems (NIPS 2009) (2009).
Linear classifiers are nearly optimal when hidden variables have diverse effects, Nader H. Bshouty, Philip M. Long, COLT, 2009.
Multiple Source Adaptation and the Renyi Divergence, Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh, Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence (UAI 2009).
On Sampling-Based Approximate Spectral Decomposition, Sanjiv Kumar, Mehryar Mohri, Ameet Talkwalkar, International Conference on Machine Learning (ICML), 2009.
Parallel Large Scale Feature Selection for Logistic Regression, Sameer Singh, Jeremy Kubica, Scott Larsen, Daria Sorokina, SIAM International Conference on Data Mining (SDM), 2009.
Polynomial semantic indexing, Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Corinna Cortes, Mehryar Mohri, Advances in Neural Information Processing Systems (NIPS 2009).
Quantum Annealing for Clustering, Kenichi Kurihara, Shu Tanaka, Seiji Miyashita, Proceedings of the 25th Annual Conference on Uncertainty in Artificial Intelligence, 2009 (to appear).
Quantum Annealing for Variational Bayes Inference, Issei Sato, Kenichi Kurihara, Shu Tanaka, Seiji Miyashita, Hiroshi Nakagawa, Proceedings of the 25th Annual Conference on Uncertainty in Artificial Intelligence, 2009 (to appear).
Rademacher Complexity Bounds for Non-I.I.D. Processes, Mehryar Mohri, Afshin Rostamizadeh, Advances in Neural Information Processing Systems (NIPS 2008), 2009.
Sampling Techniques for the Nystrom Method, Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar, Artificial Intelligence and Statistics (AISTATS), 2009.
Semi-supervised Learning of Dependency Parsers using Generalized Expectation Criteria, Gregory Druck, Gideon S. Mann, Andrew McCallum, IJCNLP-ACL, 2009.
Simple Risk Bounds for Position-Sensitive Max-Margin Ranking Algorithms, Stefan Riezler, Fabio De Bona, Proceedings of NIPS'09 Workshop on "Advances in Ranking", 2009.
Sleeping Experts and Bandits with Stochastic Action Availability and Adversarial Rewards, Varun Kanade, H. Brendan McMahan, Brent Bryan, Proceedings of the 12th International Conference on Artificial Intelligence and Statistic (AISTATS), 2009.
The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training, Dumitru Erhan, Pierre-Antoine Manzagol, Yoshua Bengio, Samy Bengio, Pascal Vincent, Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS), 2009, pp. 153-160.
Tighter Bounds for Multi-Armed Bandits with Expert Advice, H. Brendan McMahan, Matthew Streeter, Proceedings of the 22nd Annual Conference on Learning Theory (COLT), 2009.
Using the Doubling Dimension to Analyze the Generalization of Learning Algorithms, Nader H. Bshouty, Yi Li, Philip M. Long, JCSS (2009).
A Bayesian Approach to Empirical Local Linearization for Robotics, Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal, International Conference on Robotics and Automation (ICRA2008) (to appear).
A Discriminative Kernel-based Approach to Retrieval Images from Text Queries, David Grangier, Samy Bengio, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30 (2008), pp. 1371-1384.
A Machine Learning Framework for Spoken-Dialog Classification, Corinna Cortes, Patrick Haffner, Mehryar Mohri, Handbook on Speech Processing and Speech Communication, Part E: Speech recognition, 2008.
Actively Learning Level-Sets of Composite Functions, Brent Bryan, Jeff Schneider, ICML 2008: International Conference on Machine Learning.
Adaptive Martingale Boosting, Philip M. Long, Rocco A. Servedio, NIPS, 2008.
An Efficient Reduction of Ranking to Classification, Nir Ailon, Mehryar Mohri, Proceedings of The 21st Annual Conference on Learning Theory (COLT 2008).
Confidence-Weighted Linear Classification, Mark Dredze, Koby Crammer, Fernando Pereira, International Conference on Machine Learning (ICML), 2008.
Delay Learning and Polychronization for Reservoir Computing, Hélène Paugam-Moisy, Régis Martinez, Samy Bengio, Neurocomputing, vol. 71 (2008), pp. 1143-1158.
Efficient projections onto the l1-ball for learning in high dimensions, John Duchi, Shai Shalev-Shwartz, Yoram Singer, Tushar Chandra, ICML '08: Proceedings of the 25th international conference on Machine learning, 2008, pp. 272-279.
Forecasting Web Page Views: Methods and Observations, Jia Li, Andrew Moore, JMLR, vol. 9(Oct) (2008), pp. 2217-2250.
Kernel Methods for Learning Languages, Leonid Kontorovich, Corinna Cortes, Mehryar Mohri, Theoretical Computer Science, vol. 405 (2008), pp. 223-236.
Large Scale Content-Based Audio Retrieval from Text Queries, Gal Chechik, Eugene Ie, Martin Rehn, Samy Bengio, Richard F. Lyon, ACM International Conference on Multimedia Information Retrieval (MIR), 2008.
Learning Multiple Graphs for Document Recommendations, Ding Zhou, Shenghuo Zhu, Kai Yu, Xiaodan Song, Belle L. Tseng, Hongyuan Zha, C. Lee Giles, Proc. 17th International Conference on World Wide Web, 2008, pp. 141-150.
Learning sequence kernels, Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh, Proceedings of IEEE International Workshop on Machine Learning for Signal Processing, 2008.
Learning to hash: forgiving hash functions and applications Learning to hash: forgiving hash functions and applications, Shumeet Baluja, Michele Covell, Data Mining and Knowledge Discovery (2008).
Learning with weighted transducers, Corinna Cortes, Mehryar Mohri, Proceedings of the Seventh International Workshop Finite-State Methods and Natural Language Processing, 2008.
Online Learning of Complex Prediction Problems Using Simultaneous Projections, Yonatan Amit, Shai Shalev-Shwartz, Yoram Singer, J. Mach. Learn. Res., vol. 9 (2008), pp. 1399-1435.
Robust Submodular Observation Selection, Andreas Krause, H. Brendan McMahan, Carlos Guestrin, Anupam Gupta, Journal of Machine Learning Research (JMLR), vol. 9 (2008), pp. 2761-2801.
Sample Selection Bias Correction Theory, Corinna Cortes, Mehryar Mohri, Michael Riley, Afshin Rostamizadeh, Proceedings of The 19th International Conference on Algorithmic Learning Theory (ALT 2008).
Sequence Kernels for Predicting Protein Essentiality, Cyril Allauzen, Mehryar Mohri, Ameet Talwalkar, Proceedings of ICML 2008.
Stability Bounds for Non-i.i.d. Processes, Mehryar Mohri, Afshin Rostamizadeh, Advances in Neural Information Processing Systems (NIPS 2007), 2008.
Stability of Transductive Regression Algorithms, Corinna Cortes, Mehryar Mohri, Dmitry Pechyony, Ashish Rastogi, Proceedings of the Twenty-fifth International Conference on Machine Learning (ICML 2008).
Structured Learning with Approximate Inference, Alex Kulesza, Fernando Pereira, Advances in Neural Information Processing Systems 20, 2008.
Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective, Liviu Panait, Karl Tuyls, Sean Luke, Journal of Machine Learning Research (2008).
Web Page Language Identification Based on URLs, Eda Baykan, Monika Henzinger, Ingmar Weber, 34th International Conference on Very Large Data Bases (VLDB), 2008, pp. 176-188.
A General Regression Framework for Learning String-to-String Mappings, Corinna Cortes, Mehryar Mohri, Jason Weston, Predicting Structured Data, 2007.
A Generative Model for Distance Patterns in Music, Jean-Francois Paiement, Yves Grandvalet, Samy Bengio, Douglas Eck, NIPS Workshop on Music, Brain and Cognition, 2007.
A Primal-Dual Perspective of Online Learning Algorithms, Shai Shalev-Shwartz, Yoram Singer, Machine Learning, vol. 69, no. 2-3 (2007), pp. 115-142.
Automatic outlier detection: A Bayesian approach, Jo-Anne Ting, Aaron D'Souza, Stefan Schaal, International Conference on Robotics and Automation (ICRA 2007).
Boosting the area under the ROC curve, Philip M. Long, Rocco A. Servedio, NIPS, 2007.
Discriminative learning can succeed where generative learning fails, Philip M. Long, Rocco A. Servedio, Hans Ulrich Simon, Information Processing Letters, vol. 103(4) (2007), pp. 131-135.
Euclidean Embedding of Co-occurrence Data, Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby, Journal of Machine Learning Research, vol. 8 (2007), pp. 2265-2295.
Improving Embeddings by Flexible Exploitation of Side Information, Ali Ghodsi, Finnegan Southey, Dana Wilkinson, Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI-07), 2007.
Kernel Methods for Learning Languages, Leonid Kontorovich, Corinna Cortes, Mehryar Mohri, Theoretical Computer Science, vol. to appear (2007).
Lp Distance and Equivalence of Probabilistic Automata, Corinna Cortes, Mehryar Mohri, Ashish Rastogi, International Journal of Foundations of Computer Science, vol. 18 (2007).
Learning Forgiving Hash Functions: Algorithms and Large Scale Tests, Shumeet Baluja, Michele Covell, IJCAI-07: International Joint Conference on Artificial Intelligence, 2007.
Learning the Inter-frame Distance for Discriminative Template-based Keyword Detection, David Grangier, Samy Bengio, Proceedings of the International Conference Interspeech-Eurospeech, 2007.
Learning to verify branching time properties, Abhay Vardhan, Mahesh Viswanathan, Formal Methods in System Design, vol. 31, no. 1 (2007), pp. 35-61.
One-pass boosting, Zafer Barutcuoglu, Philip M. Long, Rocco A. Servedio, NIPS, 2007.
Online learning of multiple tasks with a shared loss, Ofer Dekel, Philip M. Long, Yoram Singer, JMLR, vol. 8 (2007), pp. 2233-2264.
Recursive Attribute Factoring, David Cohn, Deepak Verma, Karl Pfleger, Advances in Neural Information Processing Systems 19, 2007.
Supervised Learning of Semantic Classes for Image Annotation and Retrieval, Gustavo Carneiro, Antoni B. Chan, Pedro J. Moreno, Nuno Vasconcelos, IEEE Transactions on Pattern Analysis and Machine Intelligence (2007), pp. 394-410.
The Need for Open Source Software in Machine Learning, Soren Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Leon Bottou, Geoff Holmes, Yann LeCun, Klaus-Robert Mueller, Fernando Pereira, Carl-Edward Rasmussen, Gunnar Raetsch, Bernhard Schoelkopf, Alexander Smola, Pascal Vincent, Jason Weston, Robert C. Williamson, Journal of Machine Learning Research, vol. 8 (2007), pp. 2443-2466.
Theoretical Advantages of Lenient Learners in Multiagent Systems, Liviu Panait, Karl Tuyls, Proceedings of the Sixth International Conference on Autonomous Agents and Multi-agent Systems (AAMAS-07), 2007.
A Machine Learning Framework for Spoken-Dialog Classification, Corinna Cortes, Patrick Haffner, Mehryar Mohri, Handbook on Speech Processing and Speech Communication, Part E: Speech recognition, 2007.
An Alternative Ranking Problem for Search Engines, Corinna Cortes, Mehryar Mohri, Ashish Rastogi, Proceedings of the 6th Workshop on Experimental Algorithms (WEA 2007), pp. 1-21.
Learning Languages with Rational Kernels, Corinna Cortes, Leonid Kontorovich, Mehryar Mohri, Proceedings of The 20th Annual Conference on Computational Learning Theory (COLT 2007).
Magnitude-Preserving Ranking Algorithms, Corinna Cortes, Mehryar Mohri, Ashish Rastogi, Proceedings of the Twenty-fourth International Conference on Machine Learning (ICML 2007).
On Transductive Regression, Corinna Cortes, Mehryar Mohri, Advances in Neural Information Processing Systems (NIPS 2006), 2007.
Attribute-efficient learning of linear threshold functions under unconcentrated distributions, Philip M. Long, Rocco A. Servedio, NIPS, 2006.
Bayesian Regression with Input Noise for High-Dimensional Data, Jo-Anne Ting, Aaron D'Souza, Stefan Schaal, In Proceedings of the 23rd International Conference on Machine Learning, 2006.
Clustering graphs by weighted substructure mining, Koji Tsuda, Taku Kudo, Proceedings of the 23rd international conference on Machine learning, 2006, pp. 953-960.
Dependency trees in sub-linear time and bounded memory, Dan Pelleg, Andrew W. Moore, VLDB J., vol. 15 (2006), pp. 250-262.
Efficient Learning of Label Ranking by Soft Projections onto Polyhedra, S. Shalev-Shwartz, Y. Singer, Journal of Machine Learning Research (2006).
Online Learning meets Optimization in the Dual, S. Shalev-Shwartz, Y. Singer, Proceedings of the Nineteenth Annual Conference on Computational Learning Theory, 2006.
Online Multiclass Learning by Interclass Hypothesis Sharing, Michael Fink, Shai Shalev-Shwartz, Yoram Singer, Shimon Ullman, Proceedings of the 23rd International Conference on Machine Learning, 2006.
Online Passive Aggressive Algorithms, K. Crammer, O. Dekel, J. Keshet, S. Shalev-Shwartz, Y. Singer, Journal of Machine Learning Research, vol. 7 (2006).
PAC Learning Mixtures of Gaussians with No Separation Assumption, Jon Feldman, Ryan O'Donnell, Rocco A. Servedio, Proc. 19th Annual Conference on Learning Theory (COLT), 2006.
Predicting Electricity Distribution Feeder Failures Using Machine Learning Susceptibility Analysis, Philip Gross, Albert Boulanger, Marta Arias, David L. Waltz, Philip M. Long, Charles Lawson, Roger Anderson, Matthew Koenig, Mark Mastrocinque, William Fairechio, John A. Johnson, Serena Lee, Frank Doherty, Arthur Kressner, IAAI, 2006.
Learning Linearly Separable Languages, Leonid Kontorovich, Corinna Cortes, Mehryar Mohri, Proceedings of The 17th International Conference on Algorithmic Learning Theory (ALT 2006).
A General Regression Technique for Learning Transductions, Corinna Cortes, Mehryar Mohri, Jason Weston, Proceedings of the Twenty-Second International Conference on Machine Learning (ICML 2005).
A New Perspective on an Old Perceptron Algorithm, Shai Shalev-Shwartz, Yoram Singer, COLT, 2005, pp. 264-278.
A New Perspective on an Old Perceptron Algorithm, S. Shalev-Shwartz, Y. Singer, Proceedings of the Eighteenth Annual Conference on Computational Learning Theory, 2005.
Data-Driven Online to Batch Conversions, Ofer Dekel, Yoram Singer, NIPS, 2005.
Loss Bounds for Online Category Ranking, K. Crammer, Y. Singer, Proceedings of the Eighteenth Annual Conference on Computational Learning Theory, 2005.
Margin-Based Ranking Meets Boosting in the Middle, Cynthia Rudin, Corinna Cortes, Mehryar Mohri, Robert E. Schapire, Proc. of the 18th Annual Conference on Computational Learning Theory (COLT 2005), pp. 63-78.
Online Multiclass Learning with k-Way Limited Feedback and an Application to Utterance Classification, Hiyan Alshawi, Machine Learning, vol. 60 (2005).
Online Ranking by Projecting, K. Crammer, Y. Singer, Neural Computation, vol. 17 (2005).
Phoneme Alignment Based on Discriminative Learning, J. Keshet, S. Shalev-Shwartz, Y. Singer, D. Chazan, Interspeech, 2005.
Semi-Supervised Self-Training of Object Detection Models, Chuck Rosenberg, Martial Hebert, Henry Schneiderman, WACV/MOTION, 2005, pp. 29-36.
The Forgetron: A Kernel-Based Perceptron on a Fixed Budget, Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer, NIPS, 2005.
A Comparison of Classifiers for Detecting Emotion from Speech, Izhak Shafran, Mehryar Mohri, Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2005).
Confidence Intervals for the Area under the ROC Curve, Corinna Cortes, Mehryar Mohri, Advances in Neural Information Processing Systems (NIPS 2004), 2005.
Margin-Based Ranking Meets Boosting in the Middle, Cynthia Rudin, Corinna Cortes, Mehryar Mohri, Robert E. Schapire, Proceedings of The 18th Annual Conference on Computational Learning Theory (COLT 2005), pp. 63-78.
Moment Kernels for Regular Distributions, Corinna Cortes, Mehryar Mohri, Machine Learning, vol. 60 (2005), pp. 117-134.
Multi-Armed Bandit Algorithms and Empirical Evaluation, Joannès Vermorel, Mehryar Mohri, Proceedings of the 16th European Conference on Machine Learning (ECML 2005).
Distribution Kernels Based on Moments of Counts, Corinna Cortes, Mehryar Mohri, Proceedings of the Twenty-First International Conference on Machine Learning (ICML 2004).
Rational Kernels: Theory and Algorithms, Corinna Cortes, Patrick Haffner, Mehryar Mohri, Journal of Machine Learning Research (JMLR), vol. 5 (2004), pp. 1035-1062.