Papers
A Conditional-Gradient-Based Augmented Lagrangian Framework
Alp Yurtsever, Olivier Fercoq, Volkan Cevher
A Contrastive Divergence for Combining Variational Inference and MCMC
Francisco Ruiz, Michalis Titsias
A Convergence Theory for Deep Learning via Over-Parameterization
Zeyuan Allen-Zhu, Yuanzhi Li, Zhao Song
Action Robust Reinforcement Learning and Applications in Continuous Control
Chen Tessler, Yonathan Efroni, Shie Mannor
Active Embedding Search via Noisy Paired Comparisons
Gregory Canal, Andy Massimino, Mark Davenport et al.
Active Learning for Decision-Making from Imbalanced Observational Data
Iiris Sundin, Peter Schulam, Eero Siivola et al.
Active Learning for Probabilistic Structured Prediction of Cuts and Matchings
Sima Behpour, Anqi Liu, Brian Ziebart
Active Learning with Disagreement Graphs
Corinna Cortes, Giulia Desalvo, Mehryar Mohri et al.
Active Manifolds: A non-linear analogue to Active Subspaces
Robert Bridges, Anthony Gruber, Christopher Felder et al.
Actor-Attention-Critic for Multi-Agent Reinforcement Learning
Shariq Iqbal, Fei Sha
AdaGrad Stepsizes: Sharp Convergence Over Nonconvex Landscapes
Rachel Ward, Xiaoxia Wu, Leon Bottou
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces
Johannes Kirschner, Mojmir Mutny, Nicole Hiller et al.
Adaptive Antithetic Sampling for Variance Reduction
Hongyu Ren, Shengjia Zhao, Stefano Ermon
Adaptive Monte Carlo Multiple Testing via Multi-Armed Bandits
Martin Zhang, James Zou, David Tse
Adaptive Neural Trees
Ryutaro Tanno, Kai Arulkumaran, Daniel Alexander et al.
Adaptive Regret of Convex and Smooth Functions
Lijun Zhang, Tie-Yan Liu, Zhi-Hua Zhou
Adaptive Scale-Invariant Online Algorithms for Learning Linear Models
Michal Kempka, Wojciech Kotlowski, Manfred K. Warmuth
Adaptive Sensor Placement for Continuous Spaces
James Grant, Alexis Boukouvalas, Ryan-Rhys Griffiths et al.
Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search
Youhei Akimoto, Shinichi Shirakawa, Nozomu Yoshinari et al.
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment
Chen Huang, Shuangfei Zhai, Walter Talbott et al.
A Deep Reinforcement Learning Perspective on Internet Congestion Control
Nathan Jay, Noga Rotman, Brighten Godfrey et al.
Adjustment Criteria for Generalizing Experimental Findings
Juan Correa, Jin Tian, Elias Bareinboim
Adversarial Attacks on Node Embeddings via Graph Poisoning
Aleksandar Bojchevski, Stephan Günnemann
Adversarial camera stickers: A physical camera-based attack on deep learning systems
Juncheng Li, Frank Schmidt, Zico Kolter
Adversarial Examples Are a Natural Consequence of Test Error in Noise
Justin Gilmer, Nicolas Ford, Nicholas Carlini et al.