Experiments with time delay networks and dynamic time warping for speaker independent isolated digits recognition. - Léon Bottou; Françoise Fogelman-Soulié; Pascal Blanchet; Jean-Sylvain Liénard (EUROSPEECH, 1989)

A Framework for the Cooperation of Learning Algorithms. - Léon Bottou; Patrick Gallinari (NIPS, 1990)

Speaker-independent isolated digit recognition: Multilayer perceptrons vs. Dynamic time warping. - Léon Bottou; Françoise Fogelman-Soulié; Pascal Blanchet; Jean-Sylvain Liénard (Neural Networks, 1990)

Structural Risk Minimization for Character Recognition. - Isabelle Guyon; Vladimir Vapnik; Bernhard E. Boser; Léon Bottou; Sara A. Solla (NIPS, 1991)

Capacity control in linear classifiers for pattern recognition. - Isabelle Guyon; Vladimir Vapnik; Bernhard E. Boser; Léon Bottou; Sara A. Solla (ICPR (2), 1992)

Computer aided cleaning of large databases for character recognition. - Nada Matic; Isabelle Guyon; Léon Bottou; John S. Denker; Vladimir Vapnik (ICPR (2), 1992)

Local Learning Algorithms. - Léon Bottou; Vladimir Vapnik (Neural Comput., 1992)

Signature Verification Using A "Siamese" Time Delay Neural Network. - Jane Bromley; James W. Bentz; Léon Bottou; Isabelle Guyon; Yann LeCun; Cliff Moore; Eduard Säckinger; Roopak Shah (Int. J. Pattern Recognit. Artif. Intell., 1993)

Local Algorithms for Pattern Recognition and Dependencies Estimation. - Vladimir Vapnik; Léon Bottou (Neural Comput., 1993)

Comparison of classifier methods: a case study in handwritten digit recognition. - Léon Bottou; Corinna Cortes; John S. Denker; Harris Drucker; Isabelle Guyon; Larry D. Jackel; Yann LeCun; Urs A. Müller; Eduard Säckinger; Patrice Y. Simard; Vladimir Vapnik (ICPR (2), 1994)

Convergence Properties of the K-Means Algorithms. - Léon Bottou; Yoshua Bengio (NIPS, 1994)

Effiicient BackProp. - Yann LeCun; Léon Bottou; Genevieve B. Orr; Klaus-Robert Müller (Neural Networks: Tricks of the Trade, 1996)

Global Training of Document Processing Systems Using Graph Transformer Networks. - Léon Bottou; Yoshua Bengio; Yann LeCun (CVPR, 1997)

Reading checks with multilayer graph transformer networks. - Yann LeCun; Léon Bottou; Yoshua Bengio (ICASSP, 1997)

Browsing through High Quality Document Images with DjVu. - Patrick Haffner; Léon Bottou; Paul G. Howard; Patrice Y. Simard; Yoshua Bengio; Yann LeCun (ADL, 1998)

The Z-Coder Adaptive Binary Coder. - Léon Bottou; Paul G. Howard; Yoshua Bengio (Data Compression Conference, 1998)

Lossy Compression of Partially Masked Still Images. - Léon Bottou; Steven Pigeon (Data Compression Conference, 1998)

DjVu: a Compression Method for Distributing Scanned Documents in Color over the Internet. - Yann LeCun; Léon Bottou; Patrick Haffner; Paul G. Howard (CIC, 1998)

Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks. - Patrice Y. Simard; Léon Bottou; Patrick Haffner; Yann LeCun (NIPS, 1998)

High quality document image compression with "DjVu". - Léon Bottou; Patrick Haffner; Paul G. Howard; Patrice Y. Simard; Yoshua Bengio; Yann LeCun (J. Electronic Imaging, 1998)

Gradient-based learning applied to document recognition. - Yann LeCun; Léon Bottou; Yoshua Bengio; Patrick Haffner (Proc. IEEE, 1998)

Image and video coding-emerging standards and beyond. - Barry G. Haskell; Paul G. Howard; Yann LeCun; Atul Puri; Jörn Ostermann; M. Reha Civanlar; Lawrence R. Rabiner; Léon Bottou; Patrick Haffner (IEEE Trans. Circuits Syst. Video Technol., 1998)

DjVu: Analyzing and Compressing Scanned Documents for Internet Distribution. - Patrick Haffner; Léon Bottou; Paul G. Howard; Yann LeCun (ICDAR, 1999)

Color Documents on the Web with DJVU. - Patrick Haffner; Yann LeCun; Léon Bottou; Paul G. Howard; Pascal Vincent; Bill Riemers (ICIP (1), 1999)

Object Recognition with Gradient-Based Learning. - Yann LeCun; Patrick Haffner; Léon Bottou; Yoshua Bengio (Shape, Contour and Grouping in Computer Vision, 1999)

Vicinal Risk Minimization. - Olivier Chapelle; Jason Weston; Léon Bottou; Vladimir Vapnik (NIPS, 2000)

Masked Wavelets: Applications to Image Compression. - Steven Pigeon; Léon Bottou (Data Compression Conference, 2001)

Managing Drift in DCT-Based Scalable Video Coding. - Amy R. Reibman; Léon Bottou (Data Compression Conference, 2001)

Efficient Conversion of Digital Documents to Multilayer Raster Formats. - Léon Bottou; Patrick Haffner; Yann LeCun (ICDAR, 2001)

DCT-based scalable video coding with drift. - Amy R. Reibman; Léon Bottou; Andrea Basso 001 (ICIP (2), 2001)

Electronic Document Publishing Using DjVu. - Artem Mikheev; Luc Vincent; Michael Hawrylycz; Léon Bottou (Document Analysis Systems, 2002)

Stochastic Learning. - Léon Bottou (Advanced Lectures on Machine Learning, 2003)

Large Scale Online Learning. - Léon Bottou; Yann LeCun (NIPS, 2003)

Geometric Clustering Using the Information Bottleneck Method. - Susanne Still; William Bialek; Léon Bottou (NIPS, 2003)

Scalable video coding with managed drift. - Amy R. Reibman; Léon Bottou; Andrea Basso 001 (IEEE Trans. Circuits Syst. Video Technol., 2003)

Learning Methods for Generic Object Recognition with Invariance to Pose and Lighting. - Yann LeCun; Fu Jie Huang; Léon Bottou (CVPR (2), 2004)

Breaking SVM Complexity with Cross-Training. - Gökhan H. Bakir; Léon Bottou; Jason Weston (NIPS, 2004)

Parallel Support Vector Machines: The Cascade SVM. - Hans Peter Graf; Eric Cosatto; Léon Bottou; Igor Durdanovic; Vladimir Vapnik (NIPS, 2004)

Online (and Offline) on an Even Tighter Budget. - Jason Weston; Antoine Bordes; Léon Bottou (AISTATS, 2005)

The Huller: A Simple and Efficient Online SVM. - Antoine Bordes; Léon Bottou (ECML, 2005)

Fast Kernel Classifiers with Online and Active Learning. - Antoine Bordes; Seyda Ertekin; Jason Weston; Léon Bottou (J. Mach. Learn. Res., 2005)

Toward Automatic Phenotyping of Developing Embryos From Videos. - F. Ning; D. Delhomme; Yann LeCun; F. Piano; Léon Bottou; Paolo Emilio Barbano (IEEE Trans. Image Process., 2005)

Trading convexity for scalability. - Ronan Collobert; Fabian H. Sinz; Jason Weston; Léon Bottou (ICML, 2006)

Inference with the Universum. - Jason Weston; Ronan Collobert; Fabian H. Sinz; Léon Bottou; Vladimir Vapnik (ICML, 2006)

Large Scale Transductive SVMs. - Ronan Collobert; Fabian H. Sinz; Jason Weston; Léon Bottou (J. Mach. Learn. Res., 2006)

Learning on the border: active learning in imbalanced data classification. - Seyda Ertekin; Jian Huang 002; Léon Bottou; C. Lee Giles (CIKM, 2007)

Solving multiclass support vector machines with LaRank. - Antoine Bordes; Léon Bottou; Patrick Gallinari; Jason Weston (ICML, 2007)

Learning using Large Datasets. - Léon Bottou; Olivier Bousquet (NATO ASI Mining Massive Data Sets for Security, 2007)

The Tradeoffs of Large Scale Learning. - Léon Bottou; Olivier Bousquet (NIPS, 2007)

The Need for Open Source Software in Machine Learning. - Sören Sonnenburg; Mikio L. Braun; Cheng Soon Ong; Samy Bengio; Léon Bottou; Geoffrey Holmes 001; Yann LeCun; Klaus-Robert Müller; Fernando Pereira 003; Carl Edward Rasmussen; Gunnar Rätsch; Bernhard Schölkopf; et al. (J. Mach. Learn. Res., 2007)

Sequence Labelling SVMs Trained in One Pass. - Antoine Bordes; Nicolas Usunier; Léon Bottou (ECML/PKDD (1), 2008)

SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent. - Antoine Bordes; Léon Bottou; Patrick Gallinari (J. Mach. Learn. Res., 2009)

Large-Scale Machine Learning with Stochastic Gradient Descent. - Léon Bottou (COMPSTAT, 2010)

Erratum: SGDQN is Less Careful than Expected. - Antoine Bordes; Léon Bottou; Patrick Gallinari; Jonathan D. Chang; S. Alex Smith (J. Mach. Learn. Res., 2010)

Guarantees for Approximate Incremental SVMs. - Nicolas Usunier; Antoine Bordes; Léon Bottou (AISTATS, 2010)

L'apprentissage statistique à grande échelle. - Léon Bottou; Olivier Bousquet (Monde des Util. Anal. Données, 2010)

From Machine Learning to Machine Reasoning - Léon Bottou (CoRR, 2011)

Natural Language Processing (Almost) from Scratch. - Ronan Collobert; Jason Weston; Léon Bottou; Michael Karlen; Koray Kavukcuoglu; Pavel P. Kuksa (J. Mach. Learn. Res., 2011)

Nonconvex Online Support Vector Machines. - Seyda Ertekin; Léon Bottou; C. Lee Giles (IEEE Trans. Pattern Anal. Mach. Intell., 2011)

Batch and online learning algorithms for nonconvex neyman-pearson classification. - Gilles Gasso; Aristidis Pappaioannou; Marina Spivak; Léon Bottou (ACM Trans. Intell. Syst. Technol., 2011)

Counterfactual Reasoning and Learning Systems - Léon Bottou; Jonas Peters; Joaquin Quiñonero Candela; Denis Xavier Charles; Max Chickering; Elon Portugaly; Dipankar Ray; Patrice Y. Simard; Ed Snelson (CoRR, 2012)

Stochastic Gradient Descent Tricks. - Léon Bottou (Neural Networks: Tricks of the Trade (2nd ed.), 2012)

Efficient BackProp. - Yann LeCun; Léon Bottou; Genevieve B. Orr; Klaus-Robert Müller (Neural Networks: Tricks of the Trade (2nd ed.), 2012)

In Hindsight: Doklady Akademii Nauk SSSR, 181(4), 1968. - Léon Bottou (Empirical Inference, 2013)

Para-active learning. - Alekh Agarwal; Léon Bottou; Miroslav Dudík; John Langford 001 (CoRR, 2013)

A Functional Approximation Based Distributed Learning Algorithm. - Dhruv Mahajan 001; S. Sathiya Keerthi; S. Sundararajan; Léon Bottou (CoRR, 2013)

A Parallel SGD method with Strong Convergence. - Dhruv Mahajan 001; S. Sathiya Keerthi; S. Sundararajan; Léon Bottou (CoRR, 2013)

Counterfactual reasoning and learning systems: the example of computational advertising. - Léon Bottou; Jonas Peters; Joaquin Quiñonero Candela; Denis Xavier Charles; Max Chickering; Elon Portugaly; Dipankar Ray; Patrice Y. Simard; Ed Snelson (J. Mach. Learn. Res., 2013)

Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks. - Maxime Oquab; Léon Bottou; Ivan Laptev; Josef Sivic (CVPR, 2014)

Learning Image Embeddings using Convolutional Neural Networks for Improved Multi-Modal Semantics. - Douwe Kiela; Léon Bottou (EMNLP, 2014)

ICE: Enabling Non-Experts to Build Models Interactively for Large-Scale Lopsided Problems. - Patrice Y. Simard; David Maxwell Chickering; Aparna Lakshmiratan; Denis Xavier Charles; Léon Bottou; Carlos Garcia Jurado Suarez; David Grangier; Saleema Amershi; Johan Verwey; Jina Suh (CoRR, 2014)

Introduction to the special issue on learning semantics. - Antoine Bordes; Léon Bottou; Ronan Collobert; Dan Roth; Jason Weston; Luke Zettlemoyer (Mach. Learn., 2014)

From machine learning to machine reasoning - An essay. - Léon Bottou (Mach. Learn., 2014)

How big data changes statistical machine learning. - Léon Bottou (IEEE BigData, 2015)

Is object localization for free? - Weakly-supervised learning with convolutional neural networks. - Maxime Oquab; Léon Bottou; Ivan Laptev; Josef Sivic (CVPR, 2015)

A Lower Bound for the Optimization of Finite Sums. - Alekh Agarwal; Léon Bottou (ICML, 2015)

No Regret Bound for Extreme Bandits. - Robert Nishihara; David Lopez-Paz; Léon Bottou (AISTATS, 2016)

Unifying distillation and privileged information. - David Lopez-Paz; Léon Bottou; Bernhard Schölkopf; Vladimir Vapnik (ICLR (Poster), 2016)

Singularity of the Hessian in Deep Learning. - Levent Sagun; Léon Bottou; Yann LeCun (CoRR, 2016)

Geometrical Insights for Implicit Generative Modeling. - Léon Bottou; Martín Arjovsky; David Lopez-Paz; Maxime Oquab (Braverman Readings in Machine Learning, 2017)

Discovering Causal Signals in Images. - David Lopez-Paz; Robert Nishihara; Soumith Chintala; Bernhard Schölkopf; Léon Bottou (CVPR, 2017)

Towards Principled Methods for Training Generative Adversarial Networks. - Martín Arjovsky; Léon Bottou (ICLR, 2017)

Wasserstein Generative Adversarial Networks. - Martín Arjovsky; Soumith Chintala; Léon Bottou (ICML, 2017)

Wasserstein GAN. - Martín Arjovsky; Soumith Chintala; Léon Bottou (CoRR, 2017)

Diagonal Rescaling For Neural Networks. - Jean Lafond; Nicolas Vasilache; Léon Bottou (CoRR, 2017)

Empirical Analysis of the Hessian of Over-Parametrized Neural Networks. - Levent Sagun; Utku Evci; V. Ugur Güney; Yann N. Dauphin; Léon Bottou (ICLR (Workshop), 2018)

SING: Symbol-to-Instrument Neural Generator. - Alexandre Défossez; Neil Zeghidour; Nicolas Usunier; Léon Bottou; Francis R. Bach (NeurIPS, 2018)

Adversarial Vulnerability of Neural Networks Increases With Input Dimension. - Carl-Johann Simon-Gabriel; Yann Ollivier; Bernhard Schölkopf; Léon Bottou; David Lopez-Paz (CoRR, 2018)

WNGrad: Learn the Learning Rate in Gradient Descent. - Xiaoxia Wu; Rachel A. Ward; Léon Bottou (CoRR, 2018)

AdaGrad stepsizes: Sharp convergence over nonconvex landscapes, from any initialization. - Rachel A. Ward; Xiaoxia Wu; Léon Bottou (CoRR, 2018)

Controlling Covariate Shift using Equilibrium Normalization of Weights. - Aaron Defazio; Léon Bottou (CoRR, 2018)

An efficient distributed learning algorithm based on effective local functional approximations. - Dhruv Mahajan 001; Nikunj Agrawal; S. Sathiya Keerthi; Sundararajan Sellamanickam; Léon Bottou (J. Mach. Learn. Res., 2018)

Optimization Methods for Large-Scale Machine Learning. - Léon Bottou; Frank E. Curtis; Jorge Nocedal (SIAM Rev., 2018)

First-Order Adversarial Vulnerability of Neural Networks and Input Dimension. - Carl-Johann Simon-Gabriel; Yann Ollivier; Léon Bottou; Bernhard Schölkopf; David Lopez-Paz (ICML, 2019)

AdaGrad stepsizes: sharp convergence over nonconvex landscapes. - Rachel A. Ward; Xiaoxia Wu; Léon Bottou (ICML, 2019)

On the Ineffectiveness of Variance Reduced Optimization for Deep Learning. - Aaron Defazio; Léon Bottou (NeurIPS, 2019)

Cold Case: The Lost MNIST Digits. - Chhavi Yadav; Léon Bottou (NeurIPS, 2019)

Scaling Laws for the Principled Design, Initialization and Preconditioning of ReLU Networks. - Aaron Defazio; Léon Bottou (CoRR, 2019)

Invariant Risk Minimization. - Martín Arjovsky; Léon Bottou; Ishaan Gulrajani; David Lopez-Paz (CoRR, 2019)

Demucs: Deep Extractor for Music Sources with extra unlabeled data remixed. - Alexandre Défossez; Nicolas Usunier; Léon Bottou; Francis R. Bach (CoRR, 2019)

Music Source Separation in the Waveform Domain. - Alexandre Défossez; Nicolas Usunier; Léon Bottou; Francis R. Bach (CoRR, 2019)

Learning Representations Using Causal Invariance. - Léon Bottou (EGC, 2020)

Symplectic Recurrent Neural Networks. - Zhengdao Chen; Jianyu Zhang; Martín Arjovsky; Léon Bottou (ICLR, 2020)

On the Convergence of Adam and Adagrad. - Alexandre Défossez; Léon Bottou; Francis R. Bach; Nicolas Usunier (CoRR, 2020)

Linear unit-tests for invariance discovery. - Benjamin Aubin; Agnieszka Slowik; Martín Arjovsky; Léon Bottou; David Lopez-Paz (CoRR, 2021)

Algorithmic Bias and Data Bias: Understanding the Relation between Distributionally Robust Optimization and Data Curation. - Agnieszka Slowik; Léon Bottou (CoRR, 2021)

An Attract-Repel Decomposition of Undirected Networks. - Alexander Peysakhovich; Léon Bottou (CoRR, 2021)

On the Relation between Distributionally Robust Optimization and Data Curation (Student Abstract). - Agnieszka Slowik; Léon Bottou; Sean B. Holden; Mateja Jamnik (AAAI, 2022)

On Distributionally Robust Optimization and Data Rebalancing. - Agnieszka Slowik; Léon Bottou (AISTATS, 2022)

Rich Feature Construction for the Optimization-Generalization Dilemma. - Jianyu Zhang; David Lopez-Paz; Léon Bottou (ICML, 2022)

The Effects of Regularization and Data Augmentation are Class Dependent. - Randall Balestriero; Léon Bottou; Yann LeCun (NeurIPS, 2022)

Recycling diverse models for out-of-distribution generalization. - Alexandre Ramé; Kartik Ahuja; Jianyu Zhang; Matthieu Cord; Léon Bottou; David Lopez-Paz (CoRR, 2022)

A scaling calculus for the design and initialization of ReLU networks. - Aaron Defazio; Léon Bottou (Neural Comput. Appl., 2022)

A Simple Convergence Proof of Adam and Adagrad. - Alexandre Défossez; Léon Bottou; Francis R. Bach; Nicolas Usunier (Trans. Mach. Learn. Res., 2022)

Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need. - Vivien Cabannes; Léon Bottou; Yann LeCun; Randall Balestriero (ICCV, 2023)

Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization. - Alexandre Ramé; Kartik Ahuja; Jianyu Zhang; Matthieu Cord; Léon Bottou; David Lopez-Paz (ICML, 2023)

Learning useful representations for shifting tasks and distributions. - Jianyu Zhang; Léon Bottou (ICML, 2023)

Birth of a Transformer: A Memory Viewpoint. - Alberto Bietti; Vivien Cabannes; Diane Bouchacourt; Hervé Jégou; Léon Bottou (NeurIPS, 2023)

Borges and AI. - Léon Bottou; Bernhard Schölkopf (CoRR, 2023)

Fine-tuning with Very Large Dropout. - Jianyu Zhang; Léon Bottou (CoRR, 2024)

MagicPIG: LSH Sampling for Efficient LLM Generation. - Zhuoming Chen; Ranajoy Sadhukhan; Zihao Ye; Yang Zhou; Jianyu Zhang; Niklas Nolte; Yuandong Tian; Matthijs Douze; Léon Bottou; Zhihao Jia; Beidi Chen (ICLR, 2025)

Memory Mosaics. - Jianyu Zhang; Niklas Nolte; Ranajoy Sadhukhan; Beidi Chen; Léon Bottou (ICLR, 2025)

These Are Not All the Features You Are Looking For: A Fundamental Bottleneck in Supervised Pretraining. - Xingyu Alice Yang; Jianyu Zhang; Léon Bottou (CoRR, 2025)

Memory Mosaics at scale. - Jianyu Zhang; Léon Bottou (CoRR, 2025)