Léon Bottou
#9,407
Most Influential Person Now
French mathematician and computer scientist
Léon Bottou's AcademicInfluence.com Rankings
Léon Bottoucomputer-science Degrees
Computer Science
#470
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#488
Historical Rank
Algorithms
#40
World Rank
#40
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Machine Learning
#44
World Rank
#44
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Artificial Intelligence
#239
World Rank
#244
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Léon Bottoumathematics Degrees
Mathematics
#2491
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#3843
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Measure Theory
#325
World Rank
#491
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Computer Science Mathematics
Why Is Léon Bottou Influential?
(Suggest an Edit or Addition)According to Wikipedia, Léon Bottou is a researcher best known for his work in machine learning and data compression. His work presents stochastic gradient descent as a fundamental learning algorithm. He is also one of the main creators of the DjVu image compression technology , and the maintainer of DjVuLibre, the open source implementation of DjVu. He is the original developer of the Lush programming language.
Léon Bottou's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Gradient-based learning applied to document recognition (1998) (41173)
- Natural Language Processing (Almost) from Scratch (2011) (7182)
- Wasserstein Generative Adversarial Networks (2017) (5319)
- Large-Scale Machine Learning with Stochastic Gradient Descent (2010) (5072)
- Signature Verification Using A "Siamese" Time Delay Neural Network (1993) (3143)
- Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks (2014) (3001)
- Efficient BackProp (2012) (2877)
- Optimization Methods for Large-Scale Machine Learning (2016) (2239)
- Towards Principled Methods for Training Generative Adversarial Networks (2017) (1705)
- The Tradeoffs of Large Scale Learning (2007) (1598)
- Stochastic Gradient Descent Tricks (2012) (1519)
- Learning methods for generic object recognition with invariance to pose and lighting (2004) (1442)
- Invariant Risk Minimization (2019) (958)
- Object Recognition with Gradient-Based Learning (1999) (854)
- Is object localization for free? - Weakly-supervised learning with convolutional neural networks (2015) (838)
- Fast Kernel Classifiers with Online and Active Learning (2005) (724)
- Comparison of learning algorithms for handwritten digit recognition (1995) (668)
- Counterfactual reasoning and learning systems: the example of computational advertising (2012) (650)
- Comparison of classifier methods: a case study in handwritten digit recognition (1994) (645)
- Local Learning Algorithms (1992) (603)
- Stochastic Gradient Learning in Neural Networks (1991) (508)
- Large Scale Transductive SVMs (2006) (503)
- Convergence Properties of the K-Means Algorithms (1994) (502)
- Learning algorithms for classification: A comparison on handwritten digit recognition (1995) (492)
- Parallel Support Vector Machines: The Cascade SVM (2004) (484)
- On-line learning and stochastic approximations (1999) (429)
- Large Scale Online Learning (2003) (428)
- Learning on the border: active learning in imbalanced data classification (2007) (394)
- Trading convexity for scalability (2006) (393)
- SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent (2009) (387)
- Unifying distillation and privileged information (2015) (371)
- Stochastic Learning (2003) (371)
- Large-scale kernel machines (2007) (314)
- Support Vector Machine Solvers (2007) (297)
- Empirical Analysis of the Hessian of Over-Parametrized Neural Networks (2017) (289)
- High quality document image compression with "DjVu" (1998) (282)
- Toward automatic phenotyping of developing embryos from videos (2005) (272)
- Vicinal Risk Minimization (2000) (256)
- Improvements to the percolator algorithm for Peptide identification from shotgun proteomics data sets. (2009) (248)
- From machine learning to machine reasoning (2011) (229)
- The Need for Open Source Software in Machine Learning (2007) (219)
- Learning Image Embeddings using Convolutional Neural Networks for Improved Multi-Modal Semantics (2014) (216)
- Effiicient BackProp (1996) (211)
- Solving multiclass support vector machines with LaRank (2007) (190)
- Inference with the Universum (2006) (189)
- AdaGrad stepsizes: sharp convergence over nonconvex landscapes (2019) (176)
- Discovering Causal Signals in Images (2016) (167)
- Music Source Separation in the Waveform Domain (2019) (162)
- Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks (1998) (155)
- Symplectic Recurrent Neural Networks (2019) (153)
- On-line learning for very large data sets (2005) (146)
- Eigenvalues of the Hessian in Deep Learning: Singularity and Beyond (2016) (145)
- Nonconvex Online Support Vector Machines (2011) (135)
- Structural Risk Minimization for Character Recognition (1991) (127)
- A Lower Bound for the Optimization of Finite Sums (2014) (118)
- Global training of document processing systems using graph transformer networks (1997) (117)
- Local Algorithms for Pattern Recognition and Dependencies Estimation (1993) (115)
- The Huller: A Simple and Efficient Online SVM (2005) (95)
- A Framework for the Cooperation of Learning Algorithms (1990) (94)
- AdaGrad stepsizes: Sharp convergence over nonconvex landscapes, from any initialization (2018) (88)
- Image and video coding-emerging standards and beyond (1998) (88)
- Weakly supervised object recognition with convolutional neural networks (2014) (88)
- Breaking SVM Complexity with Cross-Training (2004) (87)
- Cold Case: The Lost MNIST Digits (2019) (85)
- Deep Convolutional Networks for Scene Parsing (2009) (85)
- On the Ineffectiveness of Variance Reduced Optimization for Deep Learning (2018) (85)
- 1 Support Vector Machine Solvers (2007) (85)
- Curiously Fast Convergence of some Stochastic Gradient Descent Algorithms (2009) (85)
- Sequence Labelling SVMs Trained in One Pass (2008) (73)
- Online (and Offline) on an Even Tighter Budget (2005) (72)
- First-Order Adversarial Vulnerability of Neural Networks and Input Dimension (2018) (71)
- WNGrad: Learn the Learning Rate in Gradient Descent (2018) (60)
- Scaling Learning Algorithms toward AI (2007) (59)
- The Z-coder adaptive binary coder (1998) (57)
- Reading checks with multilayer graph transformer networks (1997) (56)
- Singularity of the Hessian in Deep Learning (2016) (51)
- DjVu: analyzing and compressing scanned documents for Internet distribution (1999) (49)
- A Simple Convergence Proof of Adam and Adagrad (2020) (49)
- Large-Scale Learning with String Kernels (2007) (48)
- Adversarial Vulnerability of Neural Networks Increases With Input Dimension (2018) (47)
- Speaker-independent isolated digit recognition: Multilayer perceptrons vs. Dynamic time warping (1990) (45)
- Poincaré maps for analyzing complex hierarchies in single-cell data (2019) (45)
- Geometrical Insights for Implicit Generative Modeling (2017) (44)
- Geometric Clustering Using the Information Bottleneck Method (2003) (43)
- A Case Study in Handwritten Digit Recognition (1994) (42)
- SING: Symbol-to-Instrument Neural Generator (2018) (41)
- On the Convergence of Adam and Adagrad (2020) (40)
- Demucs: Deep Extractor for Music Sources with extra unlabeled data remixed (2019) (38)
- Computer aided cleaning of large databases for character recognition (1992) (38)
- Batch and online learning algorithms for nonconvex neyman-pearson classification (2011) (35)
- Scalable video coding with managed drift (2003) (33)
- Learning vector quantization, multi layer perceptron and dynamic programming: comparison and cooperation (1991) (31)
- From machine learning to machine reasoning An essay (2013) (30)
- Large-Scale Kernel Machines (Neural Information Processing) (2007) (28)
- ICE: Enabling Non-Experts to Build Models Interactively for Large-Scale Lopsided Problems (2014) (27)
- Capacity control in linear classifiers for pattern recognition (1992) (26)
- The Effects of Regularization and Data Augmentation are Class Dependent (2022) (24)
- Learning using Large Datasets (2007) (23)
- COMPARISON OF LEARNING ALGORITHMS FOR (1995) (23)
- DCT-based scalable video coding with drift (2001) (23)
- Gradient-based Learning Applied to Document Recognition Gt Graph Transformer. Gtn Graph Transformer Network. Hmm Hidden Markov Model. Hos Heuristic Oversegmentation. K-nn K-nearest Neighbor. Nn Neural Network. Ocr Optical Character Recognition. Pca Principal Component Analysis. Rbf Radial Basis Func (1998) (23)
- Linear unit-tests for invariance discovery (2021) (22)
- A general segmentation scheme for DjVu document compression (2002) (22)
- Proceedings of the 25th International Conference on Neural Information Processing Systems (2012) (22)
- PROC OF THE IEEE NOVEMBER Gradient Based Learning Applied to Document Recognition (2006) (20)
- Erratum: SGDQN is Less Careful than Expected (2010) (20)
- An efficient distributed learning algorithm based on effective local functional approximations (2013) (19)
- Browsing through high quality document images with DjVu (1998) (18)
- Experiments with time delay networks and dynamic time warping for speaker independent isolated digits recognition (1989) (18)
- Rich Feature Construction for the Optimization-Generalization Dilemma (2022) (18)
- Lossy compression of partially masked still images (1998) (17)
- Managing drift in DCT-based scalable video coding (2001) (17)
- On-line learning for very large data sets: Research Articles (2005) (17)
- Learning and Stochastic Approximations 3 Q ( z , w ) measures the economical cost ( in hard currency units ) of delivering (2012) (17)
- Graph transformer networks for image recognition (2005) (16)
- A Parallel SGD method with Strong Convergence (2013) (15)
- Sn: A simulator for connectionist models (1988) (15)
- Proceedings of the 26th Annual International Conference on Machine Learning, ICML 2009, Montreal, Quebec, Canada, June 14-18, 2009 (2009) (14)
- Large-Scale Parallel SVM Implementation (2007) (13)
- Color documents on the Web with DjVu (1999) (13)
- Algorithmic Bias and Data Bias: Understanding the Relation between Distributionally Robust Optimization and Data Curation (2021) (13)
- Proceedings of the 26th International Conference on Neural Information Processing Systems (2013) (11)
- Diagonal Rescaling For Neural Networks (2017) (11)
- Efficient conversion of digital documents to multilayer raster formats (2001) (10)
- Comparison of neural and conventional classifiers on a speech recognition problem (1989) (10)
- Guarantees for Approximate Incremental SVMs (2010) (10)
- A Functional Approximation Based Distributed Learning Algorithm (2013) (9)
- DjVu: a Compression Method for Distributing Scanned Documents in Color over the Internet (1998) (9)
- Generalized Method-of-Moments for Rank Aggregation (2013) (8)
- No Regret Bound for Extreme Bandits (2015) (7)
- The Improved Fast Gauss Transform with Applications to Machine Learning (2007) (7)
- Statistical and Machine Learning (2011) (7)
- Non-parametric Regression between Riemannian Manifolds (2009) (7)
- Making Vapnik–Chervonenkis Bounds Accurate (2015) (6)
- A Distributed Sequential Solver for Large-Scale SVMs (2007) (6)
- A Generative Model for Parts-based Object Segmentation (2012) (6)
- On Distributionally Robust Optimization and Data Rebalancing (2022) (6)
- Message Passing Inference with Chemical Reaction Networks (2013) (6)
- Para-active learning (2013) (4)
- Mean Replacement Pruning (2018) (4)
- Statistical Learning And Data Science (2017) (4)
- 1 Efficient BackProp (2012) (4)
- Proceedings of the 17th International Conference on Neural Information Processing Systems (2004) (4)
- DjVu document browsing with on-demand loading and rendering of image components (2000) (4)
- From machine learning to machine reasoning (2013) (4)
- Learning Representations Using Causal Invariance (2020) (4)
- 27th Annual Conference on Neural Information Processing Systems 2013: December 5-10, Lake Tahoe, Nevada, USA (2014) (4)
- Advances in Neural Information Processing Systems 17: Proceedings of the 2004 Conference (Bradford Books) (2005) (4)
- A unified formalism for neural net training algorithms (1992) (4)
- Scaling Laws for the Principled Design, Initialization and Preconditioning of ReLU Networks (2019) (3)
- COMPARISON AND COOPERATION OF SEVERAL CLASSIFIERS (1991) (3)
- Learning useful representations for shifting tasks and distributions (2022) (3)
- Djvu: Un systeme de compression d'images pour la distribution reticulaire de documents numerises (Djvu: An image compression system for distributing scanned document on the internet) (2000) (3)
- Marathi Handwritten Numeral Recognition using Fourier Descriptors and Normalized Chain Code (2017) (2)
- Recycling diverse models for out-of-distribution generalization (2022) (2)
- Building SVMs with Reduced Classifier Complexity (2007) (2)
- Introduction to the special issue on learning semantics (2014) (2)
- An Attract-Repel Decomposition of Undirected Networks (2021) (2)
- Tensor Decomposition for Fast Parsing with Latent-Variable PCFGs (2012) (2)
- How big data changes statistical machine learning (2015) (2)
- Document Analysis with Transducers (2015) (2)
- Fast Kernel Learning with Sparse Inverted Index (2007) (1)
- Galatea: A C-Library for Connectionist Applications (1990) (1)
- Proceedings, Twenty-Sixth International Conference on Machine Learning (2009) (1)
- Brisk Kernel Independent Component Analysis (2007) (1)
- Training Invariant SVMs Using Selective Sampling (2007) (1)
- 1 Trading Convexity for Scalability (2008) (1)
- Newton Methods for Fast Semisupervised Linear SVMs (2007) (1)
- Advances in Neural Information Processing Systems 20, Proceedings of the Twenty-First Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 3-6, 2007 (2008) (1)
- Support Vector Machine Solvers Support Vector Machine Solvers (2006) (1)
- Electronic Document Publishing Using DjVu (2002) (1)
- Poincaré maps for analyzing complex hierarchies in single-cell data (2020) (0)
- Proceedings of the 21st International Conference on Neural Information Processing Systems (2008) (0)
- Bayesian analysis of structural equation models using parameter expansion (2020) (0)
- 2014 Ieee Cis Awards (2014) (0)
- Bandit Algorithms boost Brain Computer Interfaces for motor-task selection of a brain-controlled button (2018) (0)
- New Results - Category-level object and scene recognition (2014) (0)
- Introduction to the special issue on learning semantics (2013) (0)
- Rejoinder: Making VC Bounds Accurate (2015) (0)
- Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need (2023) (0)
- Some Properties of Infinite VC-Dimension Systems Alexey Chervonenkis (2011) (0)
- Compression de donnees d'images partiellement masquees (1999) (0)
- Image and video coding—emerging standards and beyond (2001) (0)
- On the Relation between Distributionally Robust Optimization and Data Curation (Student Abstract) (2022) (0)
- Marathi Handwritten Numeral Recognition using Zernike Moments and Fourier Descriptors (2020) (0)
- Data Science, Foundations and Applications (2011) (0)
- User manual: SN: A simulator for connectionist models (1988) (0)
- In Hindsight: Doklady Akademii Nauk SSSR, 181(4), 1968 (2013) (0)
- COMPARISONOFLEARNING ALGORITHMS FORHANDWRITTEN DIGIT RECOGNITION (1995) (0)
- Pseudo-Euclidean Attract-Repel Embeddings for Undirected Graphs (2021) (0)
- Controlling Covariate Shift using Balanced Normalization of Weights (2018) (0)
- Masked Wavelets: Applications to Image Compression (2001) (0)
- Reliable K-means clustering for data mining (2009) (0)
- UvA-DARE The time-marginalized coalescent prior for hierarchical clustering The Time-Marginalized Coalescent Prior for Hierarchical Clustering (2012) (0)
- Controlling Covariate Shift using Equilibrium Normalization of Weights (2018) (0)
- Multi-Task Bayesian Optimization (2013) (0)
- A scaling calculus for the design and initialization of ReLU networks (2019) (0)
- Bilateral Contracts and Grants with Industry - MSR-Inria joint lab: Image and video mining for science andhumanities (Inria) (2014) (0)
- Pre-train, fine-tune, interpolate: a three-stage strategy for domain generalization (2022) (0)
- Approximately Efficient Online Mechanism Design (2004) (0)
- Priors for Diversity in Generative Latent Variable Models (2012) (0)
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