Papers
On Symmetric Losses for Learning from Corrupted Labels
Nontawat Charoenphakdee, Jongyeong Lee, Masashi Sugiyama
Dynamic Measurement Scheduling for Event Forecasting using Deep RL
Chun-Hao Chang, Mingjie Mai, Anna Goldenberg
Learning Action Representations for Reinforcement Learning
Yash Chandak, Georgios Theocharous, James Kostas et al.
Automated Model Selection with Bayesian Quadrature
Henry Chai, Jean-Francois Ton, Michael A. Osborne et al.
Competing Against Nash Equilibria in Adversarially Changing Zero-Sum Games
Adrian Rivera Cardoso, Jacob Abernethy, He Wang et al.
Active Embedding Search via Noisy Paired Comparisons
Gregory Canal, Andy Massimino, Mark Davenport et al.
Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances
Bugra Can, Mert Gurbuzbalaban, Lingjiong Zhu
A Quantitative Analysis of the Effect of Batch Normalization on Gradient Descent
Yongqiang Cai, Qianxiao Li, Zuowei Shen
What is the Effect of Importance Weighting in Deep Learning?
Jonathon Byrd, Zachary Lipton
Rates of Convergence for Sparse Variational Gaussian Process Regression
David Burt, Carl Edward Rasmussen, Mark Van Der Wilk
Learning Generative Models across Incomparable Spaces
Charlotte Bunne, David Alvarez-Melis, Andreas Krause et al.
Self-similar Epochs: Value in arrangement
Eliav Buchnik, Edith Cohen, Avinatan Hasidim et al.
Adversarial examples from computational constraints
Sebastien Bubeck, Yin Tat Lee, Eric Price et al.
Why do Larger Models Generalize Better? A Theoretical Perspective via the XOR Problem
Alon Brutzkus, Amir Globerson
Low Latency Privacy Preserving Inference
Alon Brutzkus, Ran Gilad-Bachrach, Oren Elisha
Understanding the Origins of Bias in Word Embeddings
Marc-Etienne Brunet, Colleen Alkalay-Houlihan, Ashton Anderson et al.
Deep Counterfactual Regret Minimization
Noam Brown, Adam Lerer, Sam Gross et al.
Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations
Daniel Brown, Wonjoon Goo, Prabhat Nagarajan et al.
Conditioning by adaptive sampling for robust design
David Brookes, Hahnbeom Park, Jennifer Listgarten
Active Manifolds: A non-linear analogue to Active Subspaces
Robert Bridges, Anthony Gruber, Christopher Felder et al.
Target Tracking for Contextual Bandits: Application to Demand Side Management
Margaux Brégère, Pierre Gaillard, Yannig Goude et al.
Coresets for Ordered Weighted Clustering
Vladimir Braverman, Shaofeng H.-C. Jiang, Robert Krauthgamer et al.
Blended Conditonal Gradients
Gábor Braun, Sebastian Pokutta, Dan Tu et al.
Unreproducible Research is Reproducible
Xavier Bouthillier, César Laurent, Pascal Vincent