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The identification of an effective function to compare examples is essential to several machine learning problems. For instance, retrieval systems entirely depend on such a function to rank the documents with respect to their estimated similarity to the submitted query. Another example is kernel-based algorithms which heavily rely on the choice of an appropriate kernel function. In most cases, the choice of the comparison function (also called, depending on the context and its mathematical properties, distance metric, similarity measure, kernel function or matching measure) is done a-priori, relying on some knowledge/assumptions specific to the task. An alternative to this a-priori selection is to learn a suitable function relying on a set of examples and some of its desired properties. This workshop is aimed at bringing together researchers interested in such a task.
Author Information
David Grangier (NEC Labs America)
Samy Bengio (Apple)
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2022 : Continuous Soft Pseudo-Labeling in ASR »
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2022 Poster: Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures »
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2021 Poster: Learnable Fourier Features for Multi-dimensional Spatial Positional Encoding »
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2021 Poster: Improving Anytime Prediction with Parallel Cascaded Networks and a Temporal-Difference Loss »
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2020 Poster: Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards »
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2020 : Dr. Samy Bengio (Google Brain) »
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2019 : Contributed Session - Spotlight Talks »
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2019 : Lunch Break and Posters »
Xingyou Song · Elad Hoffer · Wei-Cheng Chang · Jeremy Cohen · Jyoti Islam · Yaniv Blumenfeld · Andreas Madsen · Jonathan Frankle · Sebastian Goldt · Satrajit Chatterjee · Abhishek Panigrahi · Alex Renda · Brian Bartoldson · Israel Birhane · Aristide Baratin · Niladri Chatterji · Roman Novak · Jessica Forde · YiDing Jiang · Yilun Du · Linara Adilova · Michael Kamp · Berry Weinstein · Itay Hubara · Tal Ben-Nun · Torsten Hoefler · Daniel Soudry · Hsiang-Fu Yu · Kai Zhong · Yiming Yang · Inderjit Dhillon · Jaime Carbonell · Yanqing Zhang · Dar Gilboa · Johannes Brandstetter · Alexander R Johansen · Gintare Karolina Dziugaite · Raghav Somani · Ari Morcos · Freddie Kalaitzis · Hanie Sedghi · Lechao Xiao · John Zech · Muqiao Yang · Simran Kaur · Qianli Ma · Yao-Hung Hubert Tsai · Ruslan Salakhutdinov · Sho Yaida · Zachary Lipton · Daniel Roy · Michael Carbin · Florent Krzakala · Lenka Zdeborová · Guy Gur-Ari · Ethan Dyer · Dilip Krishnan · Hossein Mobahi · Samy Bengio · Behnam Neyshabur · Praneeth Netrapalli · Kris Sankaran · Julien Cornebise · Yoshua Bengio · Vincent Michalski · Samira Ebrahimi Kahou · Md Rifat Arefin · Jiri Hron · Jaehoon Lee · Jascha Sohl-Dickstein · Samuel Schoenholz · David Schwab · Dongyu Li · Sang Keun Choe · Henning Petzka · Ashish Verma · Zhichao Lin · Cristian Sminchisescu -
2019 Poster: Transfusion: Understanding Transfer Learning for Medical Imaging »
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2018 : Panel Discussion »
Rich Caruana · Mike Schuster · Ralf Schlüter · Hynek Hermansky · Renato De Mori · Samy Bengio · Michiel Bacchiani · Jason Eisner -
2018 Poster: Large Margin Deep Networks for Classification »
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2018 Poster: Insights on representational similarity in neural networks with canonical correlation »
Ari Morcos · Maithra Raghu · Samy Bengio -
2018 Poster: Content preserving text generation with attribute controls »
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2017 : Competition I: Adversarial Attacks and Defenses »
Alexey Kurakin · Ian Goodfellow · Samy Bengio · Yao Zhao · Yinpeng Dong · Tianyu Pang · Fangzhou Liao · Cihang Xie · Adithya Ganesh · Oguz Elibol -
2016 Workshop: Extreme Classification: Multi-class and Multi-label Learning in Extremely Large Label Spaces »
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2016 Poster: Can Active Memory Replace Attention? »
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2016 Poster: An Online Sequence-to-Sequence Model Using Partial Conditioning »
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2016 Poster: Reward Augmented Maximum Likelihood for Neural Structured Prediction »
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2015 Poster: Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks »
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2013 Workshop: Output Representation Learning »
Yuhong Guo · Dale Schuurmans · Richard Zemel · Samy Bengio · Yoshua Bengio · Li Deng · Dan Roth · Kilian Q Weinberger · Jason Weston · Kihyuk Sohn · Florent Perronnin · Gabriel Synnaeve · Pablo R Strasser · julien audiffren · Carlo Ciliberto · Dan Goldwasser -
2013 Poster: DeViSE: A Deep Visual-Semantic Embedding Model »
Andrea Frome · Greg Corrado · Jonathon Shlens · Samy Bengio · Jeff Dean · Marc'Aurelio Ranzato · Tomas Mikolov -
2012 Workshop: Big Data Meets Computer Vision: First International Workshop on Large Scale Visual Recognition and Retrieval »
Jia Deng · Samy Bengio · Yuanqing Lin · Li Fei-Fei -
2010 Spotlight: Feature Set Embedding for Incomplete Data »
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2010 Poster: Label Embedding Trees for Large Multi-Class Tasks »
Samy Bengio · Jason E Weston · David Grangier -
2010 Poster: Feature Set Embedding for Incomplete Data »
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2009 Poster: Group Sparse Coding »
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2009 Poster: An Online Algorithm for Large Scale Image Similarity Learning »
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2009 Poster: Polynomial Semantic Indexing »
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2007 Workshop: Efficient Machine Learning - Overcoming Computational Bottlenecks in Machine Learning (Part 2) »
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2007 Workshop: Efficient Machine Learning - Overcoming Computational Bottlenecks in Machine Learning (Part 1) »
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