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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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