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Online Unsupervised Learning of Visual Representations and Categories


Sep 13, 2021
Mengye Ren, Tyler R. Scott, Michael L. Iuzzolino, Michael C. Mozer, Richard Zemel

* 29 pages 

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Learning Neural Causal Models with Active Interventions


Sep 06, 2021
Nino Scherrer, Olexa Bilaniuk, Yashas Annadani, Anirudh Goyal, Patrick Schwab, Bernhard Schölkopf, Michael C. Mozer, Yoshua Bengio, Stefan Bauer, Nan Rosemary Ke


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Soft Calibration Objectives for Neural Networks


Jul 30, 2021
Archit Karandikar, Nicholas Cain, Dustin Tran, Balaji Lakshminarayanan, Jonathon Shlens, Michael C. Mozer, Becca Roelofs

* 17 pages total, 10 page main paper, 5 page appendix, 10 figures total, 8 figures in main paper, 2 figures in appendix 

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von Mises-Fisher Loss: An Exploration of Embedding Geometries for Supervised Learning


Mar 31, 2021
Tyler R. Scott, Andrew C. Gallagher, Michael C. Mozer


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Understanding invariance via feedforward inversion of discriminatively trained classifiers


Mar 15, 2021
Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Michael C. Mozer


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Training cascaded networks for speeded decisions using a temporal-difference loss


Feb 19, 2021
Michael L. Iuzzolino, Michael C. Mozer, Samy Bengio


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Mitigating bias in calibration error estimation


Dec 15, 2020
Rebecca Roelofs, Nicholas Cain, Jonathon Shlens, Michael C. Mozer


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Transforming Neural Network Visual Representations to Predict Human Judgments of Similarity


Oct 13, 2020
Maria Attarian, Brett D. Roads, Michael C. Mozer


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Wandering Within a World: Online Contextualized Few-Shot Learning


Jul 09, 2020
Mengye Ren, Michael L. Iuzzolino, Michael C. Mozer, Richard S. Zemel


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Compositional Embeddings for Multi-Label One-Shot Learning


Feb 12, 2020
Zeqian Li, Michael C. Mozer, Jacob Whitehill


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Exploring the Memorization-Generalization Continuum in Deep Learning


Feb 08, 2020
Ziheng Jiang, Chiyuan Zhang, Kunal Talwar, Michael C. Mozer


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Stochastic Prototype Embeddings


Sep 25, 2019
Tyler R. Scott, Karl Ridgeway, Michael C. Mozer

* 15 pages, 8 figures 

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Convolutional Bipartite Attractor Networks


Jun 15, 2019
Michael Iuzzolino, Yoram Singer, Michael C. Mozer


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Sequential mastery of multiple tasks: Networks naturally learn to learn


May 28, 2019
Guy Davidson, Michael C. Mozer


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State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations


May 26, 2019
Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Denis Kazakov, Yoshua Bengio, Michael C. Mozer

* ICML 2019 [full oral]. arXiv admin note: text overlap with arXiv:1805.08394 

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Adapted Deep Embeddings: A Synthesis of Methods for $k$-Shot Inductive Transfer Learning


Oct 27, 2018
Tyler R. Scott, Karl Ridgeway, Michael C. Mozer


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Open-Ended Content-Style Recombination Via Leakage Filtering


Sep 28, 2018
Karl Ridgeway, Michael C. Mozer


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Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding


Sep 11, 2018
Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Michael C. Mozer, Chris Pal, Yoshua Bengio

* To appear as a Spotlight presentation at NIPS 2018 

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State-Denoised Recurrent Neural Networks


May 28, 2018
Michael C. Mozer, Denis Kazakov, Robert V. Lindsey


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Learning Deep Disentangled Embeddings with the F-Statistic Loss


May 20, 2018
Karl Ridgeway, Michael C. Mozer


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Discrete Event, Continuous Time RNNs


Oct 11, 2017
Michael C. Mozer, Denis Kazakov, Robert V. Lindsey

* 21 pages 

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Learning to Generate Images with Perceptual Similarity Metrics


Jan 24, 2017
Jake Snell, Karl Ridgeway, Renjie Liao, Brett D. Roads, Michael C. Mozer, Richard S. Zemel


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Improving Human-Machine Cooperative Visual Search With Soft Highlighting


Dec 24, 2016
Ronald T. Kneusel, Michael C. Mozer


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How deep is knowledge tracing?


Jun 21, 2016
Mohammad Khajah, Robert V. Lindsey, Michael C. Mozer

* 8 pages, 2 figures 

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