Papers
Where Do You Think You're Going?: Inferring Beliefs about Dynamics from Behavior
Sid Reddy, Anca Dragan, Sergey Levine
Why Is My Classifier Discriminatory?
Irene Chen, Fredrik D Johansson, David Sontag
Why so gloomy? A Bayesian explanation of human pessimism bias in the multi-armed bandit task
Dalin Guo, Angela J. Yu
With Friends Like These, Who Needs Adversaries?
Saumya Jetley, Nicholas Lord, Philip Torr
Zero-Shot Transfer with Deictic Object-Oriented Representation in Reinforcement Learning
Ofir Marom, Benjamin Rosman
Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates
Krishnakumar Balasubramanian, Saeed Ghadimi
Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization
Sijia Liu, Bhavya Kailkhura, Pin-Yu Chen et al.
A Bayesian Data Augmentation Approach for Learning Deep Models
Toan Tran, Trung Pham, Gustavo Carneiro et al.
Accelerated consensus via Min-Sum Splitting
Patrick Rebeschini, Sekhar C Tatikonda
Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds
Yuanyuan Liu, Fanhua Shang, James Cheng et al.
Accelerated Stochastic Greedy Coordinate Descent by Soft Thresholding Projection onto Simplex
Chaobing Song, Shaobo Cui, Yong Jiang et al.
Acceleration and Averaging in Stochastic Descent Dynamics
Walid Krichene, Peter L Bartlett
Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM
Katrina Ligett, Seth Neel, Aaron Roth et al.
Action Centered Contextual Bandits
Kristjan Greenewald, Ambuj Tewari, Susan Murphy et al.
Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples
Haw-Shiuan Chang, Erik Learned-Miller, Andrew McCallum
Active Exploration for Learning Symbolic Representations
Garrett Andersen, George Konidaris
Active Learning from Peers
Keerthiram Murugesan, Jaime Carbonell
AdaGAN: Boosting Generative Models
Ilya O Tolstikhin, Sylvain Gelly, Olivier Bousquet et al.
Adaptive Accelerated Gradient Converging Method under H\"{o}lderian Error Bound Condition
Mingrui Liu, Tianbao Yang
Adaptive Active Hypothesis Testing under Limited Information
Fabio Cecchi, Nidhi Hegde
Adaptive Batch Size for Safe Policy Gradients
Matteo Papini, Matteo Pirotta, Marcello Restelli
Adaptive Bayesian Sampling with Monte Carlo EM
Anirban Roychowdhury, Srinivasan Parthasarathy
Adaptive Classification for Prediction Under a Budget
Feng Nan, Venkatesh Saligrama
Adaptive Clustering through Semidefinite Programming
Martin Royer