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Exchanging Lessons Between Algorithmic Fairness and Domain Generalization

Oct 14, 2020
Elliot Creager, J枚rn-Henrik Jacobsen, Richard Zemel


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Theoretical bounds on estimation error for meta-learning

Oct 14, 2020
James Lucas, Mengye Ren, Irene Kameni, Toniann Pitassi, Richard Zemel

* 12 pages in main paper,22 pages in appendix,4 figures total 

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SketchEmbedNet: Learning Novel Concepts by Imitating Drawings

Aug 27, 2020
Alexander Wang, Mengye Ren, Richard Zemel


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Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach

Aug 18, 2020
Martin Mladenov, Elliot Creager, Omer Ben-Porat, Kevin Swersky, Richard Zemel, Craig Boutilier


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Bayesian Few-Shot Classification with One-vs-Each P贸lya-Gamma Augmented Gaussian Processes

Jul 20, 2020
Jake Snell, Richard Zemel

* Submitted to NeurIPS 2020. 20 pages, 5 figures 

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Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data

Jun 18, 2020
Sindy L枚we, David Madras, Richard Zemel, Max Welling


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Shortcut Learning in Deep Neural Networks

May 20, 2020
Robert Geirhos, J枚rn-Henrik Jacobsen, Claudio Michaelis, Richard Zemel, Wieland Brendel, Matthias Bethge, Felix A. Wichmann

* perspective article 

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Cutting out the Middle-Man: Training and Evaluating Energy-Based Models without Sampling

Feb 14, 2020
Will Grathwohl, Kuan-Chieh Wang, Jorn-Henrik Jacobsen, David Duvenaud, Richard Zemel


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A Divergence Minimization Perspective on Imitation Learning Methods

Nov 06, 2019
Seyed Kamyar Seyed Ghasemipour, Richard Zemel, Shixiang Gu

* Published at Conference on Robot Learning (CoRL) 2019. For datasets and reproducing results please refer to https://github.com/KamyarGh/rl_swiss/blob/master/reproducing/fmax_paper.md 

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Causal Modeling for Fairness in Dynamical Systems

Sep 18, 2019
Elliot Creager, David Madras, Toniann Pitassi, Richard Zemel


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Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models

Jun 22, 2019
Guangyong Chen, Pengfei Chen, Chang-Yu Hsieh, Chee-Kong Lee, Benben Liao, Renjie Liao, Weiwen Liu, Jiezhong Qiu, Qiming Sun, Jie Tang, Richard Zemel, Shengyu Zhang

* Authors are listed in alphabetical order 

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Flexibly Fair Representation Learning by Disentanglement

Jun 06, 2019
Elliot Creager, David Madras, J枚rn-Henrik Jacobsen, Marissa A. Weis, Kevin Swersky, Toniann Pitassi, Richard Zemel

* Proceedings of the International Conference on Machine Learning (ICML), 2019 

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Conditional Generative Models are not Robust

Jun 04, 2019
Ethan Fetaya, J枚rn-Henrik Jacobsen, Richard Zemel


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High-Level Perceptual Similarity is Enabled by Learning Diverse Tasks

Mar 26, 2019
Amir Rosenfeld, Richard Zemel, John K. Tsotsos


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Learning Latent Subspaces in Variational Autoencoders

Dec 14, 2018
Jack Klys, Jake Snell, Richard Zemel

* Published as a conference paper at NeurIPS 2018. 15 pages 

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Excessive Invariance Causes Adversarial Vulnerability

Nov 01, 2018
J枚rn-Henrik Jacobsen, Jens Behrmann, Richard Zemel, Matthias Bethge


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Neural Guided Constraint Logic Programming for Program Synthesis

Oct 26, 2018
Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E. Byrd, Matthew Might, Raquel Urtasun, Richard Zemel

* To appear in NIPS 2018 

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Learning Adversarially Fair and Transferable Representations

Oct 22, 2018
David Madras, Elliot Creager, Toniann Pitassi, Richard Zemel


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Understanding the Origins of Bias in Word Embeddings

Oct 08, 2018
Marc-Etienne Brunet, Colleen Alkalay-Houlihan, Ashton Anderson, Richard Zemel


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Fairness Through Causal Awareness: Learning Latent-Variable Models for Biased Data

Sep 10, 2018
David Madras, Elliot Creager, Toniann Pitassi, Richard Zemel


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Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer

Sep 07, 2018
David Madras, Toniann Pitassi, Richard Zemel

* Accepted as a conference paper at Neural Information Processing Systems 2018 

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Reviving and Improving Recurrent Back-Propagation

Aug 13, 2018
Renjie Liao, Yuwen Xiong, Ethan Fetaya, Lisa Zhang, KiJung Yoon, Xaq Pitkow, Raquel Urtasun, Richard Zemel


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The Elephant in the Room

Aug 09, 2018
Amir Rosenfeld, Richard Zemel, John K. Tsotsos


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Aggregated Momentum: Stability Through Passive Damping

Jul 23, 2018
James Lucas, Shengyang Sun, Richard Zemel, Roger Grosse

* 10 primary pages, 11 supplementary pages, 10 figures total 

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Adversarial Distillation of Bayesian Neural Network Posteriors

Jun 27, 2018
Kuan-Chieh Wang, Paul Vicol, James Lucas, Li Gu, Roger Grosse, Richard Zemel

* accepted at ICML 2018 

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Neural Relational Inference for Interacting Systems

Jun 06, 2018
Thomas Kipf, Ethan Fetaya, Kuan-Chieh Wang, Max Welling, Richard Zemel

* ICML (2018). Code available under https://github.com/ethanfetaya/NRI 

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