Publications

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2014

Maxime Oquab, Léon Bottou, Ivan Laptev and Josef Sivic: Learning and Transferring Mid-Level Image Representations using Convolutional Neural Networks, Proceedings of Computer Vision and Pattern Recognition (CVPR), IEEE, 2014.

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Léon Bottou: From machine learning to machine reasoning: an essay, Machine Learning, 94:133-149, January 2014.

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2013

Léon Bottou, Jonas Peters, Joaquin Quiñonero-Candela, Denis X. Charles, D. Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Simard and Ed Snelson: Counterfactual Reasoning and Learning Systems: The Example of Computational Advertising, Journal of Machine Learning Research, 14(Nov):3207–3260, 2013.

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Advances in Neural Information Processing Systems 26, Edited by Chris J. C. Burges, Léon Bottou, Max Welling, Zoubin Ghahramani, and Kilian Q. Weinberger, Nips Foundation, 2013.

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Léon Bottou: In hindsight: Doklady Akademii Nauk SSSR, 181(4), 1968, in Empirical Inference. Festschrift in Honor of Vladimir N. Vapnik, Bernhard Schölkopf, Zhiyuan Luo, and Vladimir Vovk editors, Springer, 2013.

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2012

Léon Bottou, Jonas Peters, Joaquin Quiñonero-Candela, Denis X. Charles, D. Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Simard and Ed Snelson: Counterfactual Reasoning and Learning Systems, arXiv:1209.2355, September 2012.

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Léon Bottou: Stochastic Gradient Tricks, Neural Networks, Tricks of the Trade, Reloaded, 430–445, Edited by Grégoire Montavon, Genevieve B. Orr and Klaus-Robert Müller, Lecture Notes in Computer Science (LNCS 7700), Springer, 2012.

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Advances in Neural Information Processing Systems 25, Edited by Peter Bartlett, Fernando C. N. Pereira, Chris J. C. Burges, Léon Bottou, and Kilian Q. Weinberger, Nips Foundation, 2012.

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2011

Statistical Learning and Data Science, Edited by Mireille Gettler Summa, Léon Bottou, Bernard Goldfarb, Fionn Murtagh, Catherine Pardoux and Myriam Touati, CRC Computer Science & Data Analysis, Chapman & Hall, 2011.

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Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu and Pavel Kuksa: Natural Language Processing (Almost) from Scratch, Journal of Machine Learning Research, 12:2493–2537, Aug 2011.

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Léon Bottou: From Machine Learning to Machine Reasoning, arXiv:1102.1808, February 2011.

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Seyda Ertekin, Léon Bottou and C. Lee Giles: Non-Convex Online Support Vector Machines, IEEE Transactions on Pattern Recognition and Machine Intelligence, 33(2):368–381, February 2011.

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Léon Bottou and Olivier Bousquet: The Tradeoffs of Large Scale Learning, Optimization for Machine Learning, 351-368, Edited by Suvrit Sra, Sebastian Nowozin and Stephen J. Wright, MIT Press, 2011.

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Gilles Gasso, Aristidis Pappaioannou, Marina Spivak and Léon Bottou: Batch and online learning algorithms for nonconvex Neyman-Pearson classification, ACM Transaction on Intelligent System and Technologies, 2(3), 2011.

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2010

Antoine Bordes, Léon Bottou, Patrick Gallinari, Jonathan Chang and S. Alex Smith: Erratum: SGDQN is Less Careful than Expected, Journal of Machine Learning Research, 11:2229–2240, Aug 2010.

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Léon Bottou: Large-Scale Machine Learning with Stochastic Gradient Descent, Proceedings of the 19th International Conference on Computational Statistics (COMPSTAT'2010), 177–187, Edited by Yves Lechevallier and Gilbert Saporta, Paris, France, August 2010, Springer.

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Léon Bottou and Olivier Bousquet: L'apprentissage statistique à grande échelle, Revue Modulad, 42:61–73, 2010.

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Nicolas Usunier, Antoine Bordes and Léon Bottou: Guarantees for Approximate Incremental SVMs, Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 9:884-891, Edited by Yee Whye Teh and Mike Titterington, Chia Laguna Resort, Sardinia, Italy, May 2010.

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2009

Advances in Neural Information Processing Systems 21, Edited by Daphne Koller, Yoshua Bengio, Léon Bottou and Aron Culotta, Nips Foundation (http://books.nips.cc), 2009.

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David Grangier, Léon Bottou and Ronan Collobert: Deep Convolutional Networks for Scene Parsing, ICML 2009 Workshop on Learning Feature Hierarchies, June 2009.

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Marina Spivak, Jason Weston, Léon Bottou, Lukas Käll and William S. Noble: Improvements to the Percolator algorithm for peptide identification from shotgun proteomics data sets, Journal of Proteome Research, 8(7):3737–3745, July 2009.

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Proceedings of the 26th International Conference on Machine Learning (ICML 2009), Edited by Léon Bottou and Michael Littman, Omnipress, 2009.

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Antoine Bordes, Léon Bottou and Patrick Gallinari: SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent, Journal of Machine Learning Research, 10:1737–1754, 2009.

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Léon Bottou: Curiously fast convergence of some stochastic gradient descent algorithms, Unpublished open problem offered to the attendance of the SLDS 2009 conference, 2009.

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2008

Antoine Bordes, Nicolas Usunier and Léon Bottou: Sequence Labelling SVMs Trained in One Pass, Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, 146-161, Edited by Walter Daelemans, Bart Goethals and Katharina Morik, Lecture Notes in Computer Science, LNCS 5211, Springer, 2008.

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Léon Bottou and Olivier Bousquet: Learning Using Large Datasets, Mining Massive DataSets for Security, NATO ASI Workshop Series, IOS Press, Amsterdam, 2008.

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Léon Bottou and Olivier Bousquet: The Tradeoffs of Large Scale Learning, Advances in Neural Information Processing Systems, 20:161–168, Edited by J.C. Platt, D. Koller, Y. Singer and S. Roweis, NIPS Foundation (http://books.nips.cc) , 2008.

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2007

Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Léon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander Smola, Pascal Vincent, Jason Weston and Robert Williamson: The Need for Open Source Software in Machine Learning, Journal of Machine Learning Research, 8:2443-2466, October 2007.

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Seyda Ertekin, Jian Huang, Léon Bottou and C. Lee Giles: Learning on the Border: Active Learning in Imbalanced Data Classification, Proceedings of the 16th Conference on Information and Knowledge Management, CIKM2007, ACM Press, Lisboa, November 2007.

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Large Scale Kernel Machines, Edited by Léon Bottou, Olivier Chapelle, Dennis DeCoste, and Jason Weston, Neural Information Processing Series, MIT Press, Cambridge, MA., 2007.

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Antoine Bordes, Léon Bottou, Patrick Gallinari and Jason Weston: Solving MultiClass Support Vector Machines with LaRank, Proceedings of the 24th International Machine Learning Conference, 89-97, Edited by Zoubin Ghahramani, OmniPress, Corvallis, Oregon, 2007.

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Gaëlle Loosli, Stéphane Canu and Léon Bottou: Training Invariant Support Vector Machines using Selective Sampling, in Large Scale Kernel Machines, Léon Bottou, Olivier Chapelle, Dennis DeCoste, and Jason Weston editors, 301–320, MIT Press, Cambridge, MA., 2007.

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Léon Bottou and Chih-Jen Lin: Support Vector Machine Solvers, in Large Scale Kernel Machines, Léon Bottou, Olivier Chapelle, Dennis DeCoste, and Jason Weston editors, 1–28, MIT Press, Cambridge, MA., 2007.

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2006

Ronan Collobert, Fabian Sinz, Jason Weston and Léon Bottou: Large Scale Transductive SVMs, Journal of Machine Learning Research, 7:1687-1712, September 2006.

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Jason Weston, Ronan Collobert, Fabian Sinz, Léon Bottou and Vladimir Vapnik: Inference with the Universum, Proceedings of the Twenty-third International Conference on Machine Learning (ICML 2006), IMLS/ICML, 2006.

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Ronan Collobert, Jason Weston and Léon Bottou: Trading Convexity for Scalability, Proceedings of the Twenty-third International Conference on Machine Learning (ICML 2006), IMLS/ICML, 2006.

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2005

Antoine Bordes, Seyda Ertekin, Jason Weston and Léon Bottou: Fast Kernel Classifiers with Online and Active Learning, Journal of Machine Learning Research, 6:1579-1619, September 2005.

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Antoine Bordes and Léon Bottou: The Huller: a simple and efficient online SVM, Machine Learning: ECML 2005, 505-512, Lecture Notes in Artificial Intelligence, LNAI 3720, Springer Verlag, 2005.

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Advances in Neural Information Processing Systems 17, Edited by Lawrence Saul, Yair Weiss and Léon Bottou, MIT Press, Cambridge, MA., 2005.

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Feng Ning, Damien Delhomme, Yann LeCun, Fabio Piano, Léon Bottou and Paolo Emilio Barbano: Toward Automatic Phenotyping of Developing Embryos from Videos, IEEE Transactions in Image Processing, 14(9):1360-1371, September 2005.

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Léon Bottou and Yann LeCun: Graph Transformer Networks for Image Recognition, Bulletin of the International Statistical Institute (ISI), 2005.

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Jason Weston, Antoine Bordes and Léon Bottou: Online (and Offline) on an Even Tighter Budget, Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, Jan 6-8, 2005, Savannah Hotel, Barbados, 413-420, Edited by Robert G. Cowell and Zoubin Ghahramani, Society for Artificial Intelligence and Statistics, 2005.

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Gökhan Bakir, Léon Bottou and Jason Weston: Breaking SVM Complexity with Cross-Training, Advances in Neural Information Processing Systems, 17:81-88, Edited by Lawrence Saul, Yair Weiss and Léon Bottou, MIT Press, 2005.

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Hans Peter Graf, Eric Cosatto, Léon Bottou, Igor Dourdanovic and Vladimir Vapnik: Parallel Support Vector Machines: The Cascade SVM, Advances in Neural Information Processing Systems, 17, Edited by Lawrence Saul, Yair Weiss and Léon Bottou, MIT Press, 2005.

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Léon Bottou and Yann LeCun: On-line Learning for Very Large Datasets, Applied Stochastic Models in Business and Industry, 21(2):137-151, 2005.

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2004

Léon Bottou: Stochastic Learning, Advanced Lectures on Machine Learning, 146-168, Edited by Olivier Bousquet and Ulrike von Luxburg, Lecture Notes in Artificial Intelligence, LNAI 3176, Springer Verlag, Berlin, 2004.

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Yann LeCun, Léon Bottou and Jie HuangFu: Learning Methods for Generic Object Recognition with Invariance to Pose and Lighting, Proceedings of Computer Vision and Pattern Recognition (CVPR), IEEE, Washington, D.C., 2004.

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Léon Bottou and Yann LeCun: Large Scale Online Learning, Advances in Neural Information Processing Systems 16, Edited by Sebastian Thrun, Lawrence Saul and Bernhard Schölkopf, MIT Press, Cambridge, MA, 2004.

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Susanne Still, William Bialek and Léon Bottou: Geometric Clustering Using the Information Bottleneck Method, Advances in Neural Information Processing Systems 16, Edited by Sebastian Thrun, Lawrence Saul and Bernhard Schölkopf, MIT Press, Cambridge, MA, 2004.

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2003

Amy R. Reibman, Léon Bottou and Andrea Basso: Scalable video coding with managed drift, IEEE Transaction on Circuits and Systems for Video Technology, 13:131-140, February 2003.

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David W. Pan, Andrea Basso and Léon Bottou: An Iterative Algorithm for Accurate Motion Estimation in Very Low Bit Rate Video Coding, Proceedings of the GSPx & ISPC 2003 (The International Signal Processing Conference), Dallas, March 2003.

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2002

Léon Bottou and Noboru Murata: Stochastic Approximations and Efficient Learning, The Handbook of Brain Theory and Neural Networks, Second edition,, Edited by M. A. Arbib, The MIT Press, Cambridge, MA, 2002.

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Artem Mikheev, Luc Vincent, Mike Hawrylycz and Léon Bottou: Electronic Document Publishing using DjVu, Proceedings of the IAPR International Workshop on Document Analysis (DAS'02), Princeton, NJ, August 2002.

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Patrick Haffner, Léon Bottou, Yann Le Cun and Luc Vincent: A General Segmentation Scheme for DjVu Document Compression, Proceedings of the International Symposium on Mathematical Morphology (ISMM'02), CSIRO publications, Sydney, Australia, April 2002.

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2001

Yann Le Cun, Léon Bottou, Andrei Erofeev, Patrick Haffner and Bill W. Riemers: DjVu document browsing with on-demand loading and rendering of image components, Internet Imaging, San Jose, January 2001.

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Amy R. Reibman and Léon Bottou: Managing drift in DCT-based scalable video coding, Proceedings IEEE Data Compression Conference 2001, IEEE, Snowbird, Utah, April 2001.

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Amy R. Reibman, Léon Bottou and Andrea Basso: DCT-based scalable video coding with drift, Proceedings of International Conference on Image Processing 2001, 989-992, IEEE, Thessaloniki, Greece, October 2001.

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Léon Bottou, Patrick Haffner and Yann Le Cun: Efficient Conversion of Digital Documents to Multilayer Raster Formats, Proceedings of the Sixth International Conference on Document Analysis and Recognition, 444-448, IEEE, Seattle, September 2001.

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Yann Le Cun, Léon Bottou, Patrick Haffner, Jeffery Triggs, Bill Riemers and Luc Vincent: Overview of the DjVu Document Compression Technology, Proceedings of the Symposium on Document Image Understanding Technologies (SDIUT'01), 119–122, Columbia, MD, April 2001.

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2000

Léon Bottou, Patrick Haffner, Yann Le Cun, Paul Howard and Pascal Vincent: DjVu: Un Système de Compression d'Images pour la Distribution Réticulaire de Documents Numérisés, Actes de la Conférence Internationale Francophone sur l'Ecrit et le Document, Lyon, France, July 2000.

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Olivier Chapelle, Jason Weston, Léon Bottou and Vladimir Vapnik: Vicinal Risk Minimization, Advances in Neural Information Processing Systems, 12, MIT Press, Denver, 2000.

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1999

Patrice Simard, Léon Bottou, Patrick Haffner and Yann Le Cun: Boxlets: a fast convolution algorithm for neural networks and signal processing, Advances in Neural Information Processing Systems, 11, MIT Press, Denver, 1999.

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Patrick Haffner, Léon Bottou, Paul G. Howard and Yann Le Cun: DjVu : Analyzing and Compressing Scanned Documents for Internet Distribution. , Proceedings of the International Conference on Document Analysis and Recognition., 625–628, 1999.

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Yann Le Cun, Patrick Haffner, Léon Bottou and Yoshua Bengio: Object Recognition with Gradient-Based Learning, Feature Grouping, Edited by David Forsyth, Springer Verlag, 1999.

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Patrick Haffner, Yann Le Cun, Léon Bottou, Paul Howard and Pascal Vincent: Color Documents on the Web with DjVu, Proceedings of the International Conference on Image Processing, 1:239-243, Kobe, Japan, October 1999.

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Léon Bottou, Yann Le Cun and Vladimir Vapnik: Predicting Learning Curves without the Ground Truth Hypothesis, Technical Report, May 1999.

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1998

Léon Bottou, Paul G. Howard and Yoshua Bengio: The Z-Coder Adaptive Binary Coder, Proceedings IEEE Data Compression Conference 1998, IEEE, Snowbird, April 1998.

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Léon Bottou and Steven Pigeon: Lossy Compression of Partially Masked Still Images, Proceedings of IEEE Data Compression Conference, Snowbird, UT, April 1998.

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Léon Bottou, Patrick Haffner, Paul G. Howard, Patrice Simard, Yoshua Bengio and Yann Le Cun: High Quality Document Image Compression with DjVu, Journal of Electronic Imaging, 7(3):410-425, 1998.

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Patrick Haffner, Léon Bottou, Paul G. Howard, Patrice Simard, Yoshua Bengio and Yann Le Cun: Browsing through High Quality Document Images with DjVu, Proceedings of IEEE Advances in Digital Libraries'98, 309-318, IEEE, Santa Barbara, CA, April 1998.

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Léon Bottou: Online Algorithms and Stochastic Approximations, Online Learning and Neural Networks, Edited by David Saad, Cambridge University Press, Cambridge, UK, 1998.

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Yann Le Cun, Léon Bottou, Yoshua Bengio and Patrick Haffner: Gradient Based Learning Applied to Document Recognition, Proceedings of IEEE, 86(11):2278-2324, 1998.

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Barry Haskell, Paul Howard, Yann Le Cun, Atul Puri, Joern Ostermann, M. Reha Civanlar, Larry Rabiner, Léon Bottou and Patrick Haffner: Image and video coding - Emerging standards and beyond, IEEE Transaction on Circuits and Systems for Video Technology, 8(7):814-837, November 1998.

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Yann Le Cun, Léon Bottou, Genevieve B. Orr and Klaus-Robert Müller: Efficient Backprop, Neural Networks, Tricks of the Trade, Lecture Notes in Computer Science LNCS 1524, Springer Verlag, 1998.

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Yann Le Cun, Léon Bottou, Patrick Haffner and Paul G. Howard: DjVu: a compression method for distributing scanned documents in color over the internet, Sixth Color Imaging Conference: Color Science, Systems and Applications, 220-223, IST, Scottsdale, Arizona, November 1998.

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1997

Yann Le Cun, Léon Bottou and Yoshua Bengio: Reading Checks with graph transformer networks, International Conference on Acoustics, Speech, and Signal Processing, 1:151-154, IEEE, Munich, 1997.

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Léon Bottou, Yann Le Cun and Yoshua Bengio: Global Training of Document Processing Systems using Graph Transformer Networks, Proceedings of Computer Vision and Pattern Recognition (CVPR), 489-493, IEEE, Puerto-Rico, 1997.

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Léon Bottou: La mise en oeuvre des idées de V. N. Vapnik, Statistique et méthodes neuronales, Dunod, Paris, 1997.

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1995

Yann Le Cun, Lawrence D. Jackel, Léon Bottou, Corinna Cortes, John S. Denker, Harris Drucker, Isabelle Guyon, Urs A. Muller, Eduard Sackinger, Patrice Simard and Vladimir N. Vapnik: Learning Algorithms For Classification: A Comparison On Handwritten Digit Recognition, Neural Networks: The Statistical Mechanics Perspective, 261-276, Edited by J. H. Oh, C. Kwon and S. Cho, World Scientific, 1995.

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Léon Bottou and Yoshua Bengio: Convergence Properties of the KMeans Algorithm, Advances in Neural Information Processing Systems, 7, MIT Press, Denver, 1995.

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1994

Léon Bottou, Corinna Cortes and Vladimir Vapnik: On the Effective VC Dimension., Neuroprose (bottou.effvc.ps.Z), 1994.

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Léon Bottou, Corinna Cortes, John S. Denker, Harris Drucker, Isabelle Guyon, Lawrence D. Jackel, Yann Le Cun, Urs A. Muller, Eduard Säckinger, Patrice Simard and Vladimir Vapnik: Comparison of classifier methods: a case study in handwritten digit recognition, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Conference B: Computer Vision & Image Processing., 2:77-82, IEEE, Jerusalem, October 1994.

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1993

Vladimir N. Vapnik and Léon Bottou: Local Algorithms for Pattern Recognition and Dependencies Estimation, Neural Computation, 5(6):893-909, 1993.

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Jame Bromley, Jim W. Bentz, Léon Bottou, Isabelle Guyon, Yann Le Cun, C. Moore, Eduard Säckinger and Roopak Shah: Signature Verification using a Siamese Time Delay Neural Network, International Journal of Pattern Recognition and Artificial Intelligence, 7(4), 1993.

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1992

Isabelle Guyon, Vladimir Vapnik, Bernhardt E. Boser, Léon Bottou and Sara A. Solla: Capacity control in linear classifiers for pattern recognition, Proceedings of the 11th IAPR International Conference on Pattern Recognition, Conference B: Pattern Recognition Methodology and Systems , II:385-388, IEEE, September 1992.

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Isabelle Guyon, Vladimir N. Vapnik, Bernhardt E. Boser, Léon Bottou and Sara A. Solla: Structural Risk Minimization for Character Recognition, Advances in Neural Information Processing Systems, 4, Morgan Kaufman, Denver, 1992.

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Léon Bottou and Vladimir N. Vapnik: Local Learning Algorithms, Neural Computation, 4(6):888-900, 1992.

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Nada Matic, Isabelle Guyon, Léon Bottou, John S. Denker and Vladimir N. Vapnik: Computer Aided Cleaning of Large Databases for Character Recognition, Proceedings of the 11th IAPR International Conference on Pattern Recognition, Conference B: Pattern Recognition Methodology and Systems , II:330-333, IEEE, La Hague, September 1992.

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Léon Bottou and Patrick Gallinari: A unified formalism for neural net training algorithms, Proceedings of the International Joint Conference on Neural Networks, 4:7-12, IEEE, June 1992.

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1991

Léon Bottou: Une Approche théorique de l'Apprentissage Connexionniste: Applications à la Reconnaissance de la Parole, Ph.D. thesis, Université de Paris XI, Orsay, France, 1991.

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Léon Bottou: Stochastic Gradient Learning in Neural Networks, Proceedings of Neuro-Nîmes 91, EC2, Nimes, France, 1991.

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Xavier Driancourt, Léon Bottou and Patrick Gallinari: Learning Vector Quantization, Multi Layer Perceptron and Dynamic Time Warping: Comparison and Cooperation, Proceedings of the International Joint Conference on Neural Networks, Seattle, 1991.

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Xavier Driancourt, Léon Bottou and Patrick Gallinari: Comparison and Cooperation of Several Classifiers, Proceedings of the International Conference on Artificial Neural Networks, Helsinki, 1991.

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Léon Bottou and Patrick Gallinari: A Framework for the Cooperation of Learning Algorithms, Advances in Neural Information Processing Systems, 3, Edited by D. Touretzky and R. Lippmann, Morgan Kaufmann, Denver, 1991.

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1990

Léon Bottou, Françoise Fogelman Soulié, Pascal Blanchet and Jean Sylvain Lienard: Speaker independent isolated digit recognition: Multilayer perceptron vs Dynamic Time Warping, Neural Networks, 3:453-465, 1990.

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Xavier Driancourt and Léon Bottou: TDNN-Extracted features, Proceedings of Neuro Nimes 90, EC2, Nimes, France, 1990.

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Carlos Mejia, Léon Bottou and Françoise Fogelman Soulié: Galatea: A library for connectionist applications, Proceedings of the International Neural Networks Conference, INNC'90, 1:9-13, Paris, 1990.

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1989

M. D. Bedworth, Léon Bottou, John S. Bridle, Franck Fallside, L. Flynn, Françoise Fogelman Soulié, K.M. Ponting and Richard W. Prager: Comparison of neural and conventional classifiers on a speech recognition problem, Proceedings of IEE 1st International Conference on Artificial Neural Networks, London, 1989.

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Léon Bottou, Françoise. Fogelman Soulié, Pascal Blanchet and Jean Sylvain Lienard: Experiments with Time Delay Networks and Dynamic Time Warping for Speaker Independent Isolated Digit Recognition, Proceedings of EuroSpeech 89, 2:537-540, Paris, France, 1989.

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1988

Léon Bottou: Reconnaissance de la parole par reseaux connexionnistes, Proceedings of Neuro Nimes 88, 197-218, Nimes, France, 1988.

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Léon Bottou and Yann Le Cun: SN: A Simulator for Connectionist Models, Proceedings of NeuroNimes 88, 371-382, Nimes, France, 1988.

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papers.txt · Last modified: 2014/09/07 21:21 by leonb
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