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2020 – today
- 2023
[c66]Alexandre Ramé, Kartik Ahuja, Jianyu Zhang, Matthieu Cord, Léon Bottou, David Lopez-Paz:
Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization. ICML 2023: 28656-28679- [c65]Jianyu Zhang, Léon Bottou:
Learning useful representations for shifting tasks and distributions. ICML 2023: 40830-40850 - [i38]Vivien Cabannes, Léon Bottou, Yann LeCun, Randall Balestriero:
Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need. CoRR abs/2303.15256 (2023) - [i37]Alberto Bietti, Vivien Cabannes, Diane Bouchacourt, Hervé Jégou, Léon Bottou:
Birth of a Transformer: A Memory Viewpoint. CoRR abs/2306.00802 (2023) - 2022
- [j25]Aaron Defazio
, Léon Bottou:
A scaling calculus for the design and initialization of ReLU networks. Neural Comput. Appl. 34(17): 14807-14821 (2022) - [j24]Alexandre Défossez, Léon Bottou, Francis R. Bach, Nicolas Usunier:
A Simple Convergence Proof of Adam and Adagrad. Trans. Mach. Learn. Res. 2022 (2022) - [c64]Agnieszka Slowik, Léon Bottou, Sean B. Holden, Mateja Jamnik:
On the Relation between Distributionally Robust Optimization and Data Curation (Student Abstract). AAAI 2022: 13053-13054 - [c63]Agnieszka Slowik, Léon Bottou:
On Distributionally Robust Optimization and Data Rebalancing. AISTATS 2022: 1283-1297 - [c62]Jianyu Zhang, David Lopez-Paz, Léon Bottou:
Rich Feature Construction for the Optimization-Generalization Dilemma. ICML 2022: 26397-26411 - [c61]Randall Balestriero, Léon Bottou, Yann LeCun:
The Effects of Regularization and Data Augmentation are Class Dependent. NeurIPS 2022 - [i36]Jianyu Zhang, David Lopez-Paz, Léon Bottou:
Rich Feature Construction for the Optimization-Generalization Dilemma. CoRR abs/2203.15516 (2022) - [i35]Randall Balestriero, Léon Bottou, Yann LeCun:
The Effects of Regularization and Data Augmentation are Class Dependent. CoRR abs/2204.03632 (2022) - [i34]Jianyu Zhang, Léon Bottou:
Learning useful representations for shifting tasks and distributions. CoRR abs/2212.07346 (2022) - [i33]Alexandre Ramé, Kartik Ahuja, Jianyu Zhang, Matthieu Cord, Léon Bottou, David Lopez-Paz:
Recycling diverse models for out-of-distribution generalization. CoRR abs/2212.10445 (2022) - 2021
- [i32]Benjamin Aubin, Agnieszka Slowik, Martín Arjovsky, Léon Bottou, David Lopez-Paz:
Linear unit-tests for invariance discovery. CoRR abs/2102.10867 (2021) - [i31]Agnieszka Slowik, Léon Bottou:
Algorithmic Bias and Data Bias: Understanding the Relation between Distributionally Robust Optimization and Data Curation. CoRR abs/2106.09467 (2021) - [i30]Alexander Peysakhovich, Léon Bottou:
An Attract-Repel Decomposition of Undirected Networks. CoRR abs/2106.09671 (2021) - 2020
- [c60]Léon Bottou:
Learning Representations Using Causal Invariance. EGC 2020: 5-6 - [c59]Zhengdao Chen, Jianyu Zhang, Martín Arjovsky, Léon Bottou:
Symplectic Recurrent Neural Networks. ICLR 2020 - [i29]Alexandre Défossez, Léon Bottou, Francis R. Bach, Nicolas Usunier:
On the Convergence of Adam and Adagrad. CoRR abs/2003.02395 (2020)
2010 – 2019
- 2019
- [c58]Carl-Johann Simon-Gabriel, Yann Ollivier, Léon Bottou, Bernhard Schölkopf, David Lopez-Paz:
First-Order Adversarial Vulnerability of Neural Networks and Input Dimension. ICML 2019: 5809-5817 - [c57]Rachel Ward, Xiaoxia Wu, Léon Bottou:
AdaGrad stepsizes: sharp convergence over nonconvex landscapes. ICML 2019: 6677-6686 - [c56]Aaron Defazio, Léon Bottou:
On the Ineffectiveness of Variance Reduced Optimization for Deep Learning. NeurIPS 2019: 1753-1763 - [c55]Chhavi Yadav, Léon Bottou:
Cold Case: The Lost MNIST Digits. NeurIPS 2019: 13443-13452 - [i28]Chhavi Yadav, Léon Bottou:
Cold Case: The Lost MNIST Digits. CoRR abs/1905.10498 (2019) - [i27]Aaron Defazio, Léon Bottou:
Scaling Laws for the Principled Design, Initialization and Preconditioning of ReLU Networks. CoRR abs/1906.04267 (2019) - [i26]Martín Arjovsky, Léon Bottou, Ishaan Gulrajani, David Lopez-Paz:
Invariant Risk Minimization. CoRR abs/1907.02893 (2019) - [i25]Alexandre Défossez, Nicolas Usunier, Léon Bottou, Francis R. Bach:
Demucs: Deep Extractor for Music Sources with extra unlabeled data remixed. CoRR abs/1909.01174 (2019) - [i24]Zhengdao Chen, Jianyu Zhang, Martín Arjovsky, Léon Bottou:
Symplectic Recurrent Neural Networks. CoRR abs/1909.13334 (2019) - [i23]Alexandre Défossez, Nicolas Usunier, Léon Bottou, Francis R. Bach:
Music Source Separation in the Waveform Domain. CoRR abs/1911.13254 (2019) - 2018
- [j23]Dhruv Mahajan, Nikunj Agrawal, S. Sathiya Keerthi, Sundararajan Sellamanickam, Léon Bottou:
An efficient distributed learning algorithm based on effective local functional approximations. J. Mach. Learn. Res. 19: 74:1-74:37 (2018) - [j22]Léon Bottou, Frank E. Curtis, Jorge Nocedal:
Optimization Methods for Large-Scale Machine Learning. SIAM Rev. 60(2): 223-311 (2018) - [c54]Levent Sagun, Utku Evci, V. Ugur Güney, Yann N. Dauphin, Léon Bottou:
Empirical Analysis of the Hessian of Over-Parametrized Neural Networks. ICLR (Workshop) 2018 - [c53]Alexandre Défossez, Neil Zeghidour, Nicolas Usunier, Léon Bottou, Francis R. Bach:
SING: Symbol-to-Instrument Neural Generator. NeurIPS 2018: 9055-9065 - [i22]Carl-Johann Simon-Gabriel, Yann Ollivier, Bernhard Schölkopf, Léon Bottou, David Lopez-Paz:
Adversarial Vulnerability of Neural Networks Increases With Input Dimension. CoRR abs/1802.01421 (2018) - [i21]Xiaoxia Wu, Rachel Ward, Léon Bottou:
WNGrad: Learn the Learning Rate in Gradient Descent. CoRR abs/1803.02865 (2018) - [i20]Rachel Ward, Xiaoxia Wu, Léon Bottou:
AdaGrad stepsizes: Sharp convergence over nonconvex landscapes, from any initialization. CoRR abs/1806.01811 (2018) - [i19]Alexandre Défossez, Neil Zeghidour, Nicolas Usunier, Léon Bottou, Francis R. Bach:
SING: Symbol-to-Instrument Neural Generator. CoRR abs/1810.09785 (2018) - [i18]Aaron Defazio, Léon Bottou:
On the Ineffectiveness of Variance Reduced Optimization for Deep Learning. CoRR abs/1812.04529 (2018) - [i17]Aaron Defazio, Léon Bottou:
Controlling Covariate Shift using Equilibrium Normalization of Weights. CoRR abs/1812.04549 (2018) - 2017
- [c52]Léon Bottou, Martín Arjovsky, David Lopez-Paz, Maxime Oquab:
Geometrical Insights for Implicit Generative Modeling. Braverman Readings in Machine Learning 2017: 229-268 - [c51]David Lopez-Paz, Robert Nishihara, Soumith Chintala, Bernhard Schölkopf, Léon Bottou:
Discovering Causal Signals in Images. CVPR 2017: 58-66 - [c50]Martín Arjovsky, Léon Bottou:
Towards Principled Methods for Training Generative Adversarial Networks. ICLR 2017 - [c49]Martín Arjovsky, Soumith Chintala, Léon Bottou:
Wasserstein Generative Adversarial Networks. ICML 2017: 214-223 - [i16]Martín Arjovsky, Léon Bottou:
Towards Principled Methods for Training Generative Adversarial Networks. CoRR abs/1701.04862 (2017) - [i15]Martín Arjovsky, Soumith Chintala, Léon Bottou:
Wasserstein GAN. CoRR abs/1701.07875 (2017) - [i14]Jean Lafond, Nicolas Vasilache, Léon Bottou:
Diagonal Rescaling For Neural Networks. CoRR abs/1705.09319 (2017) - [i13]Levent Sagun, Utku Evci, V. Ugur Güney, Yann N. Dauphin, Léon Bottou:
Empirical Analysis of the Hessian of Over-Parametrized Neural Networks. CoRR abs/1706.04454 (2017) - [i12]Léon Bottou, Martín Arjovsky, David Lopez-Paz, Maxime Oquab:
Geometrical Insights for Implicit Generative Modeling. CoRR abs/1712.07822 (2017) - 2016
- [c48]Robert Nishihara, David Lopez-Paz, Léon Bottou:
No Regret Bound for Extreme Bandits. AISTATS 2016: 259-267 - [c47]David Lopez-Paz, Léon Bottou, Bernhard Schölkopf, Vladimir Vapnik:
Unifying distillation and privileged information. ICLR (Poster) 2016 - [i11]David Lopez-Paz, Robert Nishihara, Soumith Chintala, Bernhard Schölkopf, Léon Bottou:
Discovering Causal Signals in Images. CoRR abs/1605.08179 (2016) - [i10]Léon Bottou, Frank E. Curtis, Jorge Nocedal:
Optimization Methods for Large-Scale Machine Learning. CoRR abs/1606.04838 (2016) - [i9]Levent Sagun, Léon Bottou, Yann LeCun:
Singularity of the Hessian in Deep Learning. CoRR abs/1611.07476 (2016) - 2015
- [c46]Léon Bottou:
How big data changes statistical machine learning. IEEE BigData 2015: 1 - [c45]Maxime Oquab, Léon Bottou, Ivan Laptev, Josef Sivic:
Is object localization for free? - Weakly-supervised learning with convolutional neural networks. CVPR 2015: 685-694 - [c44]Alekh Agarwal, Léon Bottou:
A Lower Bound for the Optimization of Finite Sums. ICML 2015: 78-86 - [i8]Robert Nishihara, David Lopez-Paz, Léon Bottou:
No Regret Bound for Extreme Bandits. CoRR abs/1508.02933 (2015) - 2014
- [j21]Antoine Bordes, Léon Bottou, Ronan Collobert, Dan Roth, Jason Weston, Luke Zettlemoyer:
Introduction to the special issue on learning semantics. Mach. Learn. 94(2): 127-131 (2014) - [j20]Léon Bottou:
From machine learning to machine reasoning - An essay. Mach. Learn. 94(2): 133-149 (2014) - [c43]Maxime Oquab, Léon Bottou, Ivan Laptev, Josef Sivic:
Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks. CVPR 2014: 1717-1724 - [c42]Douwe Kiela, Léon Bottou:
Learning Image Embeddings using Convolutional Neural Networks for Improved Multi-Modal Semantics. EMNLP 2014: 36-45 - [i7]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:
ICE: Enabling Non-Experts to Build Models Interactively for Large-Scale Lopsided Problems. CoRR abs/1409.4814 (2014) - 2013
- [j19]Léon Bottou, Jonas Peters, Joaquin Quiñonero Candela, Denis Xavier Charles, Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Y. Simard, Ed Snelson:
Counterfactual reasoning and learning systems: the example of computational advertising. J. Mach. Learn. Res. 14(1): 3207-3260 (2013) - [c41]Léon Bottou:
In Hindsight: Doklady Akademii Nauk SSSR, 181(4), 1968. Empirical Inference 2013: 3-5 - [e4]Christopher J. C. Burges, Léon Bottou, Zoubin Ghahramani, Kilian Q. Weinberger:
Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States. 2013 [contents] - [i6]Alekh Agarwal, Léon Bottou, Miroslav Dudík, John Langford:
Para-active learning. CoRR abs/1310.8243 (2013) - [i5]Dhruv Mahajan, S. Sathiya Keerthi, S. Sundararajan, Léon Bottou:
A Functional Approximation Based Distributed Learning Algorithm. CoRR abs/1310.8418 (2013) - [i4]Dhruv Mahajan, S. Sathiya Keerthi, S. Sundararajan, Léon Bottou:
A Parallel SGD method with Strong Convergence. CoRR abs/1311.0636 (2013) - 2012
- [p3]Yann LeCun, Léon Bottou, Genevieve B. Orr, Klaus-Robert Müller:
Efficient BackProp. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 9-48 - [p2]Léon Bottou:
Stochastic Gradient Descent Tricks. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 421-436 - [e3]Peter L. Bartlett, Fernando C. N. Pereira, Christopher J. C. Burges, Léon Bottou, Kilian Q. Weinberger:
Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012, Lake Tahoe, Nevada, United States. 2012 [contents] - [i3]Léon Bottou, Jonas Peters, Joaquin Quiñonero Candela, Denis Xavier Charles, Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Y. Simard, Ed Snelson:
Counterfactual Reasoning and Learning Systems. CoRR abs/1209.2355 (2012) - 2011
- [j18]Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu, Pavel P. Kuksa:
Natural Language Processing (Almost) from Scratch. J. Mach. Learn. Res. 12: 2493-2537 (2011) - [j17]Seyda Ertekin, Léon Bottou, C. Lee Giles:
Nonconvex Online Support Vector Machines. IEEE Trans. Pattern Anal. Mach. Intell. 33(2): 368-381 (2011) - [j16]Gilles Gasso, Aristidis Pappaioannou, Marina Spivak, Léon Bottou:
Batch and online learning algorithms for nonconvex neyman-pearson classification. ACM Trans. Intell. Syst. Technol. 2(3): 28:1-28:19 (2011) - [i2]Léon Bottou:
From Machine Learning to Machine Reasoning. CoRR abs/1102.1808 (2011) - [i1]Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu, Pavel P. Kuksa:
Natural Language Processing (almost) from Scratch. CoRR abs/1103.0398 (2011) - 2010
- [j15]Antoine Bordes, Léon Bottou, Patrick Gallinari, Jonathan D. Chang, S. Alex Smith:
Erratum: SGDQN is Less Careful than Expected. J. Mach. Learn. Res. 11: 2229-2240 (2010) - [j14]Léon Bottou, Olivier Bousquet:
L'apprentissage statistique à grande échelle. Monde des Util. Anal. Données 42: 61-73 (2010) - [c40]Léon Bottou:
Large-Scale Machine Learning with Stochastic Gradient Descent. COMPSTAT 2010: 177-186 - [c39]Nicolas Usunier, Antoine Bordes, Léon Bottou:
Guarantees for Approximate Incremental SVMs. AISTATS 2010: 884-891
2000 – 2009
- 2009
- [j13]Antoine Bordes, Léon Bottou, Patrick Gallinari:
SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent. J. Mach. Learn. Res. 10: 1737-1754 (2009) - [e2]Andrea Pohoreckyj Danyluk, Léon Bottou, Michael L. Littman:
Proceedings of the 26th Annual International Conference on Machine Learning, ICML 2009, Montreal, Quebec, Canada, June 14-18, 2009. ACM International Conference Proceeding Series 382, ACM 2009, ISBN 978-1-60558-516-1 [contents] - [e1]Daphne Koller, Dale Schuurmans, Yoshua Bengio, Léon Bottou:
Advances in Neural Information Processing Systems 21, Proceedings of the Twenty-Second Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 8-11, 2008. Curran Associates, Inc. 2009 [contents] - 2008
- [c38]Antoine Bordes, Nicolas Usunier, Léon Bottou:
Sequence Labelling SVMs Trained in One Pass. ECML/PKDD (1) 2008: 146-161 - 2007
- [j12]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 J. Smola, Pascal Vincent, Jason Weston, Robert C. Williamson:
The Need for Open Source Software in Machine Learning. J. Mach. Learn. Res. 8: 2443-2466 (2007) - [c37]Seyda Ertekin, Jian Huang, Léon Bottou, C. Lee Giles:
Learning on the border: active learning in imbalanced data classification. CIKM 2007: 127-136 - [c36]Antoine Bordes, Léon Bottou, Patrick Gallinari, Jason Weston:
Solving multiclass support vector machines with LaRank. ICML 2007: 89-96 - [c35]Léon Bottou, Olivier Bousquet:
Learning using Large Datasets. NATO ASI Mining Massive Data Sets for Security 2007: 15-26 - [c34]Léon Bottou, Olivier Bousquet:
The Tradeoffs of Large Scale Learning. NIPS 2007: 161-168 - 2006
- [j11]Ronan Collobert, Fabian H. Sinz, Jason Weston, Léon Bottou:
Large Scale Transductive SVMs. J. Mach. Learn. Res. 7: 1687-1712 (2006) - [c33]Ronan Collobert, Fabian H. Sinz, Jason Weston, Léon Bottou:
Trading convexity for scalability. ICML 2006: 201-208 - [c32]Jason Weston, Ronan Collobert, Fabian H. Sinz, Léon Bottou, Vladimir Vapnik:
Inference with the Universum. ICML 2006: 1009-1016 - 2005
- [j10]Antoine Bordes, Seyda Ertekin, Jason Weston, Léon Bottou:
Fast Kernel Classifiers with Online and Active Learning. J. Mach. Learn. Res. 6: 1579-1619 (2005) - [j9]F. Ning, D. Delhomme, Yann LeCun, F. Piano, Léon Bottou, Paolo Emilio Barbano:
Toward Automatic Phenotyping of Developing Embryos From Videos. IEEE Trans. Image Process. 14(9): 1360-1371 (2005) - [c31]Jason Weston, Antoine Bordes, Léon Bottou:
Online (and Offline) on an Even Tighter Budget. AISTATS 2005 - [c30]Antoine Bordes, Léon Bottou:
The Huller: A Simple and Efficient Online SVM. ECML 2005: 505-512 - 2004
- [c29]Yann LeCun, Fu Jie Huang, Léon Bottou:
Learning Methods for Generic Object Recognition with Invariance to Pose and Lighting. CVPR (2) 2004: 97-104 - [c28]Gökhan H. Bakir, Léon Bottou, Jason Weston:
Breaking SVM Complexity with Cross-Training. NIPS 2004: 81-88 - [c27]Hans Peter Graf, Eric Cosatto, Léon Bottou, Igor Durdanovic, Vladimir Vapnik:
Parallel Support Vector Machines: The Cascade SVM. NIPS 2004: 521-528 - 2003
- [j8]Amy R. Reibman, Léon Bottou, Andrea Basso:
Scalable video coding with managed drift. IEEE Trans. Circuits Syst. Video Technol. 13(2): 131-140 (2003) - [c26]Léon Bottou:
Stochastic Learning. Advanced Lectures on Machine Learning 2003: 146-168 - [c25]Léon Bottou, Yann LeCun:
Large Scale Online Learning. NIPS 2003: 217-224 - [c24]Susanne Still, William Bialek, Léon Bottou:
Geometric Clustering Using the Information Bottleneck Method. NIPS 2003: 1165-1172 - 2002
- [c23]Artem Mikheev, Luc Vincent, Michael Hawrylycz, Léon Bottou:
Electronic Document Publishing Using DjVu. Document Analysis Systems 2002: 480-490 - 2001
- [c22]Amy R. Reibman, Léon Bottou:
Managing Drift in DCT-Based Scalable Video Coding. Data Compression Conference 2001: 351- - [c21]Steven Pigeon, Léon Bottou:
Masked Wavelets: Applications to Image Compression. Data Compression Conference 2001: 510 - [c20]Léon Bottou, Patrick Haffner, Yann LeCun:
Efficient Conversion of Digital Documents to Multilayer Raster Formats. ICDAR 2001: 444-449 - [c19]Amy R. Reibman, Léon Bottou, Andrea Basso:
DCT-based scalable video coding with drift. ICIP (2) 2001: 989-992 - 2000
- [c18]Olivier Chapelle, Jason Weston, Léon Bottou, Vladimir Vapnik:
Vicinal Risk Minimization. NIPS 2000: 416-422
1990 – 1999
- 1999
- [c17]Patrick Haffner, Léon Bottou, Paul G. Howard, Yann LeCun:
DjVu: Analyzing and Compressing Scanned Documents for Internet Distribution. ICDAR 1999: 625-628 - [c16]Patrick Haffner, Yann LeCun, Léon Bottou, Paul G. Howard, Pascal Vincent, Bill Riemers:
Color Documents on the Web with DJVU. ICIP (1) 1999: 239-243 - [c15]Yann LeCun, Patrick Haffner, Léon Bottou, Yoshua Bengio:
Object Recognition with Gradient-Based Learning. Shape, Contour and Grouping in Computer Vision 1999: 319- - 1998
- [j7]Léon Bottou, Patrick Haffner, Paul G. Howard, Patrice Y. Simard, Yoshua Bengio, Yann LeCun:
High quality document image compression with "DjVu". J. Electronic Imaging 7(3): 410-425 (1998) - [j6]Yann LeCun, Léon Bottou, Yoshua Bengio, Patrick Haffner:
Gradient-based learning applied to document recognition. Proc. IEEE 86(11): 2278-2324 (1998) - [j5]Barry G. Haskell, Paul G. Howard, Yann LeCun, Atul Puri, Jörn Ostermann, M. Reha Civanlar, Lawrence R. Rabiner, Léon Bottou, Patrick Haffner:
Image and video coding-emerging standards and beyond. IEEE Trans. Circuits Syst. Video Technol. 8(7): 814-837 (1998) - [c14]Patrick Haffner, Léon Bottou, Paul G. Howard, Patrice Y. Simard, Yoshua Bengio, Yann LeCun:
Browsing through High Quality Document Images with DjVu. ADL 1998: 309-318 - [c13]Léon Bottou, Paul G. Howard, Yoshua Bengio:
The Z-Coder Adaptive Binary Coder. Data Compression Conference 1998: 13-22 - [c12]Léon Bottou, Steven Pigeon:
Lossy Compression of Partially Masked Still Images. Data Compression Conference 1998: 528 - [c11]Yann LeCun, Léon Bottou, Patrick Haffner, Paul G. Howard:
DjVu: a Compression Method for Distributing Scanned Documents in Color over the Internet. CIC 1998: 220-223 - [c10]Patrice Y. Simard, Léon Bottou, Patrick Haffner, Yann LeCun:
Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks. NIPS 1998: 571-577 - 1997
- [c9]Léon Bottou, Yoshua Bengio, Yann LeCun:
Global Training of Document Processing Systems Using Graph Transformer Networks. CVPR 1997: 489-494 - [c8]Yann LeCun, Léon Bottou, Yoshua Bengio:
Reading checks with multilayer graph transformer networks. ICASSP 1997: 151-154 - 1996
- [p1]Yann LeCun, Léon Bottou, Genevieve B. Orr, Klaus-Robert Müller:
Effiicient BackProp. Neural Networks: Tricks of the Trade 1996: 9-50 - 1994
- [c7]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:
Comparison of classifier methods: a case study in handwritten digit recognition. ICPR (2) 1994: 77-82 - [c6]Léon Bottou, Yoshua Bengio:
Convergence Properties of the K-Means Algorithms. NIPS 1994: 585-592 - 1993
- [j4]