Publications

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2023

Alberto Bietti, Vivien Cabannes, Diane Bouchacourt, Herve Jegou and Leon Bottou: Birth of a Transformer: A Memory Viewpoint, arXiv preprint arXiv:2306.00802, 2023.

Vivien Cabannes, Leon Bottou, Yann Lecun and Randall Balestriero: Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need, arXiv preprint arXiv:2303.15256, 2023.

Jianyu Zhang and Léon Bottou: Learning useful representations for shifting tasks and distributions, International Conference on Machine Learning, 40830–40850, PMLR, 2023.

Alexandre Rame, Kartik Ahuja, Jianyu Zhang, Matthieu Cord, Leon Bottou and David Lopez-Paz: Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization, Proceedings of the 40th International Conference on Machine Learning, 202:28656–28679, Edited by Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato and Jonathan Scarlett, Proceedings of Machine Learning Research, PMLR, 23–29 Jul 2023.

2022

Randall Balestriero, Leon Bottou and Yann LeCun: The Effects of Regularization and Data Augmentation are Class Dependent, Advances in Neural Information Processing Systems, 35:37878–37891, Edited by S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho and A. Oh, Curran Associates, Inc., 2022.

Jianyu Zhang, David Lopez-Paz and Léon Bottou: Rich feature construction for the optimization-generalization dilemma, International Conference on Machine Learning, 26397–26411, PMLR, 2022.

Agnieszka Słowik and Léon Bottou: On Distributionally Robust Optimization and Data Rebalancing, Proc. AIStats 2022, Feb 2022.

Alexandre Défossez, Leon Bottou, Francis Bach and Nicolas Usunier: A Simple Convergence Proof of Adam and Adagrad, Transactions on Machine Learning Research, 2022.

Alexander Peysakhovich and Leon Bottou: Pseudo-Euclidean Attract-Repel Embeddings for Undirected Graphs, arXiv preprint arXiv:2106.09671, 2021.

2021

Benjamin Aubin, Agnieszka Słowik, Martin Arjovsky, Léon Bottou and David Lopez-Paz: Linear unit-tests for invariance discovery, arXiv preprint arXiv:2102.10867, 2021.

2020

Anna Klimovskaia, David Lopez-Paz, Léon Bottou and Maximilian Nickel: Poincaré maps for analyzing complex hierarchies in single-cell data, Nature Communications, 11(1):2966, 2020.

Emmanuelle Claeys, Myriam Maumy-Bertrand and Léon Bottou: Causalité et apprentissage automatique, Statistique et Causalité, Journées d’'Etude en Statistique 2018, Technip, 2020.

2019

Martin Arjovsky, Léon Bottou, Ishaan Gulrajani and David Lopez-Paz: Invariant Risk Minimization, arXiv:1907.02893, 2019.

Chhavi Yadav and Léon Bottou: Cold Case: The Lost MNIST Digits, Advances in Neural Information Processing Systems 32, 13443–13452, Edited by H. Wallach, H. Larochelle, A. Beygelzimer, i F. d'Alché-Buc, E. Fox and R. Garnett, Curran Associates, Inc., 2019.

Rachel Ward, Xiaoxia Wu and Leon Bottou: AdaGrad Stepsizes: Sharp Convergence Over Nonconvex Landscapes, Proceedings of the 36th International Conference on Machine Learning, 97:6677–6686, Edited by Kamalika Chaudhuri and Ruslan Salakhutdinov, Proceedings of Machine Learning Research, PMLR, Long Beach, California, USA, 09–15 Jun 2019.

Carl-Johann Simon-Gabriel, Yann Ollivier, Leon Bottou, Bernhard Schölkopf and David Lopez-Paz: First-Order Adversarial Vulnerability of Neural Networks and Input Dimension, Proceedings of the 36th International Conference on Machine Learning, 97:5809–5817, Edited by Kamalika Chaudhuri and Ruslan Salakhutdinov, Proceedings of Machine Learning Research, Long Beach, California, USA, 2019.

2018

Dhruv Mahajan, Nikunj Agrawal, S Sathiya Keerthi, Sundararajan Sellamanickam and Léon Bottou: An efficient distributed learning algorithm based on effective local functional approximations, The Journal of Machine Learning Research, 19(1):2942–2978, 2018.

Alexandre Defossez, Neil Zeghidour, Nicolas Usunier, Leon Bottou and Francis Bach: SING: Symbol-to-Instrument Neural Generator, Advances in Neural Information Processing Systems 31, 9041–9051, Edited by S. Bengio, H. Wallach, H. Larochelle, K. Grauman, N. Cesa-Bianchi and R. Garnett, Curran Associates, Inc., 2018.

Léon Bottou, Frank E. Curtis and Jorge Nocedal: Optimization Methods for Large-Scale Machine Learning, Siam Reviews, 60(2):223-311, 2018.

Léon Bottou, Martin Arjovsky, David Lopez-Paz and Maxime Oquab: Geometrical Insights for Implicit Generative Modeling, Braverman Readings in Machine Learning: Key Ideas from Inception to Current State, 229–268, Edited by Ilya Muchnik Lev Rozonoer, Boris Mirkin, LNAI Vol 11100, Springer, 2018.

Levent Sagun, Utku Evci, Veli Uğur Güney, Yann Dauphin and Léon Bottou: Empirical Analysis of the Hessian of Over-Parametrized Neural Networks, Sixth International Conference on Learning Representations (ICLR), Workshop paper, 2018.

2017

Léon Bottou: Foreword. Perceptrons. Reissue of the 1988 expanded edition. By Marvin L. Minsky and Seymour A. Papert. MIT Press. Cambridge, MA., September 2017.

Jean Lafond, Nicolas Vasilache and Léon Bottou: Diagonal Rescaling For Neural Networks, arXiV:1705.09319, 2017.

Martin Arjovsky, Soumith Chintala and Léon Bottou: Wasserstein Generative Adversarial Networks, Proceedings of the 34nd International Conference on Machine Learning, ICML 2017, Sydney, Australia, 7-9 August, 2017, 2017.

David Lopez-Paz, Robert Nishihara, Soumith Chintalah, Bernhard Schölkopf and Léon Bottou: Discovering Causal Signals in Images, Proceedings of Computer Vision and Pattern Recognition (CVPR), IEEE, 2017.

Martin Arjovsky and Léon Bottou: Towards principled methods for training generative adversarial networks, International Conference on Learning Representations (ICLR 2017), 2017.

2016

Léon Bottou, Frank E. Curtis and Jorge Nocedal: Optimization Methods for Large-Scale Machine Learning, arXiv:1606.04838, June 2016.

David Lopez-Paz, Leon Bottou, Bernhard Schölkopf and Vladimir Vapnik: Unifying distillation and privileged information, International Conference on Learning Representations (ICLR 2016), 2016.

Robert Nishihara, David Lopez-Paz and Leon Bottou: No Regret Bound for Extreme Bandits, Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 259-267, 2016.

2015

Alekh Agarwal and Léon Bottou: A Lower Bound for the Optimization of Finite Sums, Proceedings of the 32nd International Conference on Machine Learning, ICML 2015, Lille, France, 6-11 July 2015, 78–86, 2015.

more... (with erratum)

Maxime Oquab, Léon Bottou, Josef Sivic and Ivan Laptev: Is object localization for free? – Weakly-supervised learning with convolutional neural networks, Proceedings of Computer Vision and Pattern Recognition (CVPR), IEEE, 2015.

Léon Bottou: Making Vapnik-Chervonenkis bounds accurate, Measures of Complexity. Festschrift for Alexey Chervonenkis, Springer, 2015.

2014

Douwe Kiela and Léon Bottou: Learning Image Embeddings using Convolutional Neural Networks for Improved Multi-Modal Semantics, Proceedings of EMNLP 2014, Doha, Qatar, 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.

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

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.

Advances in Neural Information Processing Systems 26 (NIPS 2013), Edited by Chris J. C. Burges, Léon Bottou, Max Welling, Zoubin Ghahramani, and Kilian Q. Weinberger, Curran Associates, Inc., 2013.

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.

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.

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.

Advances in Neural Information Processing Systems 25 (NIPS 2012), Edited by Peter Bartlett, Fernando C. N. Pereira, Chris J. C. Burges, Léon Bottou, and Kilian Q. Weinberger, Curran Associates, Inc., 2012.

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.

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.

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

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.

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.

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.

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.

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.

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

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.

2009

Advances in Neural Information Processing Systems 21 (NIPS 2008), Edited by Daphne Koller, Yoshua Bengio, Léon Bottou and Aron Culotta, Nips Foundation (http://books.nips.cc), 2009.

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

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.

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

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

more... erratum...

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

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.

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

Léon Bottou and Olivier Bousquet: The Tradeoffs of Large Scale Learning, Advances in Neural Information Processing Systems 20 (NIPS 2007), 161–168, Edited by J.C. Platt, D. Koller, Y. Singer and S. Roweis, NIPS Foundation (http://books.nips.cc) , 2008.

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.

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.

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

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.

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.

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.

2006

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

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.

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.

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.

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.

Advances in Neural Information Processing Systems 17 (NIPS 2004), Edited by Lawrence Saul, Yair Weiss and Léon Bottou, MIT Press, Cambridge, MA., 2005.

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.

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

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.

Gökhan Bakir, Léon Bottou and Jason Weston: Breaking SVM Complexity with Cross-Training, Advances in Neural Information Processing Systems 17 (NIPS 2004), 81-88, Edited by Lawrence Saul, Yair Weiss and Léon Bottou, MIT Press, 2005.

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 (NIPS 2004), 521-528, Edited by Lawrence Saul, Yair Weiss and Léon Bottou, MIT Press, 2005.

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

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.

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.

Léon Bottou and Yann LeCun: Large Scale Online Learning, Advances in Neural Information Processing Systems 16 (NIPS 2003), Edited by Sebastian Thrun, Lawrence Saul and Bernhard Schölkopf, MIT Press, Cambridge, MA, 2004.

Susanne Still, William Bialek and Léon Bottou: Geometric Clustering Using the Information Bottleneck Method, Advances in Neural Information Processing Systems 16 (NIPS 2003), Edited by Sebastian Thrun, Lawrence Saul and Bernhard Schölkopf, MIT Press, Cambridge, MA, 2004.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Olivier Chapelle, Jason Weston, Léon Bottou and Vladimir Vapnik: Vicinal Risk Minimization, Advances in Neural Information Processing Systems 13 (NIPS 2000), 416-422, MIT Press, Denver, 2001.

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 (NIPS 1998), 571-577, MIT Press, Denver, 1999.

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.

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.

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.

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

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.

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

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.

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.

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

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.

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.

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.

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.

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.

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.

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

1996

Léon Bottou, Yoshua Bengio and Yann LeCun: Document Analysis with Transducers, July 1996.

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.

Léon Bottou and Yoshua Bengio: Convergence Properties of the KMeans Algorithm, Advances in Neural Information Processing Systems 7 (NIPS 1994), 585-592, MIT Press, Denver, 1995.

1994

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

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.

1993

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

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.

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.

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 (NIPS 1991), 471-479, Morgan Kaufman, Denver, 1992.

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

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.

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.

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.

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

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.

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

Léon Bottou and Patrick Gallinari: A Framework for the Cooperation of Learning Algorithms, Advances in Neural Information Processing Systems 3 (NIPS 1990), Edited by D. Touretzky and R. Lippmann, 781-788, Morgan Kaufmann, Denver, 1991.

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.

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

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.

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.

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.

1988

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

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