Done. There are many resources out there, I have tried to not make a long list of them! .. . & Op. Their, This "Cited by" count includes citations to the following articles in Scholar. Other papers on word tagging with neural networks: Natural Language Processing (Almost) from Scratch by Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu and Pavel Kuksa across words most … The Journal of Machine Learning Research 17 (1), 2096-2030. I also spent two years in the machine learning group Optimization as a Model for Few-Shot Learning, (2016), Sachin Ravi and Hugo Larochelle. William Fedus1 2 Prajit Ramachandran 1Rishabh Agarwal Yoshua Bengio2 3 Hugo Larochelle1 4 Mark Rowland 5Will Dabney Abstract Experience replay is central to off-policy algo-rithms in deep reinforcement learning (RL), but there remain significant gaps in our understanding. Hugo Larochelle Departement d’informatique´ Universite de Sherbrooke´ [email protected] Stanislas Lauly D´epartement d’informatique Universite de Sherbrooke´ [email protected] Abstract We describe a new model for learning meaningful representations of text docu-ments from an unlabeled collection of documents. Medical Image Analysis. Hugo Larochelle and Iain Murray. The general Hamid Palangi, [email protected] Here is my reading list for deep learning. ��y����ݩ���P����n'��-tP�i�Qf��������Y�K� ���,����f�r_��j|tU����0�'�(b�e1���q��%8�Pk��v�+�_���������e��|�e�!H)� Hugo Larochelle Iain Murray Department of Computer Science University of Toronto Toronto, Canada School of Informatics University of Edinburgh Edinburgh, Scotland Abstract We describe a new approach for modeling the distribution of high-dimensional vectors of dis-crete variables. Hugo Larochelle [email protected] D epartement d’informatique, Universit e de Sherbrooke Qu ebec, Canada, J1K 2R1 Fran˘cois Laviolette [email protected] Mario Marchand [email protected] D epartement d’informatique et de g enie logiciel, Universit e Laval Qu ebec, Canada, G1V 0A6 We therefore present a systematic and extensive analysis of experience replay in Q-learning meth-ods, focusing on … Ruslan Salakhutdinov, Hugo Larochelle ; JMLR W&CP 9:693-700, 2010. Volume 35, January 2017, Pages 18-31. Hugo Larochelle, Yoshua Bengio, Jérôme Louradour and Pascal Lamblin, Journal of Machine Learning Research , 10(Jan): 1--40, 2009 Deep Learning using Robust Interdependent Codes [ pdf ] Few-Shot Learning: Thoughts On Where We Should Be Going. Centre-Ville, Montral, Qubec, H3C 3J7, Canada Abstract Previous work has shown that the difficul-ties in learning deep generative or discrim- Academic Profile User Profile. M Ren, E Triantafillou, S Ravi, J Snell, K Swersky, JB Tenenbaum, ... S Chandar AP, S Lauly, H Larochelle, M Khapra, B Ravindran, VC Raykar, ... Advances in neural information processing systems 27, 1853-1861, AAAI Conference on Artificial Intelligence 1 (2), 2.2, New articles related to this author's research, Professor of computer science, University of Montreal, Mila, IVADO, CIFAR, Facebook AI Research; U. Montreal (Professor, Computer Sc. Étude de la pertinence de métriques statistiques pour la détection de termes dans un document Hugo Larochelle and Philippe Langlais, NSERC Internship report at RALI lab, Département d'informatique et recherche opérationnelle, Université de Montréal, été 2002. Hugo Larochelle [email protected] Yoshua Bengio [email protected] Pierre-Antoine Manzagol [email protected] Universit´e de Montr´eal, Dept. ); MILA; CIFAR, Professor, Polytechnique Montréal & Mila, Element AI, Canada CIFAR AI Chair, professeur d'informatique, Université Laval, Université Laval, Associate member at MILA, School of Informatics, University of Edinburgh, Professor of Computer Science, University of Toronto. PDF Restore Delete Forever. Learning Neural Causal Models from Unknown Interventions Nan Rosemary Ke * 1;2, Olexa Bilaniuk , Anirudh Goyal , Stefan Bauer5, Hugo Larochelle4, Bernhard Schölkopf5, Michael C. Mozer4, Chris Pal1 ;2 3, Yoshua Bengio1y 1 Mila, Université de Montréal, 2 Mila, Polytechnique Montréal, 3 Element AI 4 Google AI, 5 Max Planck Institute for Intelligent Systems, yCIFAR Senior Fellow. View Larochelle - Neural Networks 2 - DLSS 2017.pdf from AA 1Neural Networks Hugo Larochelle ( @hugo_larochelle ) Google Brain Neural Networks Types of learning problems 3 SUPERVISED Exploring strategies for training deep neural networks. Sachin Ravi and Hugo Larochelle Twitter, Cambridge, USA fsachinr,[email protected] ABSTRACT Though deep neural networks have shown great success in the large data domain, they generally perform poorly on few-shot learning tasks, where a classifier has to quickly generalize after seeing very few examples from each class. IRO, Universit´e de Montr´eal I’m Hugo Larochelle and it’s in my role of General Chair that I’m happy to welcome you to the NeurIPS 2020 conference! Each week is associated with explanatory video clips and recommended readings. Feedforward neural network 2. Few-shot learning is the problem of learning new tasks from little amounts of labeled data. My main area of expertise is deep learning. Google Brain. Deep learning 8. 1. 9000. I've put this course together while teaching an in-class version of it at the Université de Sherbrooke. Generalization in RL •Need some way to scale to large state spaces •Important for planning •Important for learning Hugo Larochelle [email protected] Yoshua Bengio [email protected] Jer´ omeˆ Louradour [email protected] Pascal Lamblin [email protected] D´epartement d’informatique et de recherche oper´ ationnelle Universite´ de Montreal´ 2920, chemin de la Tour Montreal,´ Qu´ebec, Canada, H3T 1J8 Editor: Leon´ Bottou Abstract Deep multi-layer neural … . This is a graduate-level course, which covers basic neural networks as well as more advanced topics, including: Deep learning. Introduction. 0. New articles by this author. Includes work with Ruslan Salakhutdinov and Hugo Larochelle. Autoencoders 7. Yoshua Bengio, Pascal Lamblin, Dan Popovici and Hugo Larochelle Dept. [ Abstract and code , PDF , DjVu , GoogleViewer , BibTeX , Discussion ] c 2009 Hugo Larochelle, Yoshua Bengio, J´er omeˆ Louradour and Pascal Lamblin. Extracting and Composing Robust Features with Denoising Autoencoders Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pierre-Antoine Manzagol Dept. Greedy layer-wise training of deep networks, Extracting and composing robust features with denoising autoencoders, Practical bayesian optimization of machine learning algorithms, Domain-adversarial training of neural networks, Brain tumor segmentation with deep neural networks, Optimization as a model for few-shot learning, Autoencoding beyond pixels using a learned similarity metric. Hugo Larochelle, Christian Jauvin et Yoshua Bengio, Affiche présentée à la conférence Échanges Québec de MITACS, Montréal, Canada, 2003. Hugo Larochelle [email protected] Yoshua Bengio [email protected] Dept. Hugo Larochelle Department of Computer Science University of Sherbrooke [email protected] Ryan P. Adams School of Engineering and Applied Sciences Harvard University [email protected] Abstract The use of machine learning algorithms frequently involves careful tuning of learning parameters and model hyperparameters. Follow this author. Y Shen, NC Harris, S Skirlo, M Prabhu, T Baehr-Jones, M Hochberg, ... International Conference on Artificial Intelligence and Statistics, M Germain, K Gregor, I Murray, H Larochelle, International Conference on Machine Learning, 881-889. Machine Learning Artificial Intelligence. A Neural Autoregressive Topic Model by Hugo Larochelle and Stanislas Lauly. LAROCHELLE, BENGIO, LOURADOUR AND LAMBLIN ements and parameters required to represent some functions (Bengio and Le Cun, 2007; Bengio, 2007). All Since 2015; Citations: 37972: 34350: h-index: 52: 50: i10-index: 88: 86: 0. Res. I currently lead the Google Brain group in Montreal. Unfortunately, this tuning is of- ten … Log in AMiner. Training neural networks 3. LONG BEACH CA | DEC 4 - 9 | NIPS.CC NIPS 2017 TUTORIALS - DEC 4TH Statistical Relational Artificial Intelligence: Logic, Probability and Computation Luc De Raedt, … Hugo Larochelle Departement d’informatique´ Universite de Sherbrooke´ [email protected] November 13, 2012 Abstract Math for my slides “Natural language processing”. Try again later. Optimization as a Model for Few-Shot Learning, (2016), Sachin Ravi and Hugo Larochelle. Restricted Boltzmann machine 6. Get my own profile. from Hugo Larochelle, Google Brain. PhD thesis, … Hugo Larochelle, Christian Jauvin and Yoshua Bengio, Poster presented at MITACS Quebec Interchange, Montréal, Canada, 2003. . M Havaei, A Davy, D Warde-Farley, A Biard, A Courville, Y Bengio, C Pal, ... ABL Larsen, SK Sønderby, H Larochelle, O Winther, International conference on machine learning, 1558-1566, H Larochelle, Y Bengio, J Louradour, P Lamblin, Journal of machine learning research 10 (1), H Larochelle, D Erhan, A Courville, J Bergstra, Y Bengio, Proceedings of the 24th international conference on Machine learning, 473-480, Proceedings of the 25th international conference on Machine learning, 536-543, L Yao, A Torabi, K Cho, N Ballas, C Pal, H Larochelle, A Courville, Proceedings of the IEEE international conference on computer vision, 4507-4515. C $��nH�ЈH��:ڕ:�|%W;�efK1"�3��p�S�$�z�_�������e'Dpt��i�r�q�c?0�@����o���O"K. Extracting and Composing Robust Features with Denoising Autoencoders Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pierre-Antoine Manzagol Dept. This year is a unique time for the conference. Hugo Larochelle. IRO, CP 6128, Succ. Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion. 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