Papers
Provably Efficient Maximum Entropy Exploration
Elad Hazan, Sham Kakade, Karan Singh et al.
Provably efficient RL with Rich Observations via Latent State Decoding
Simon Du, Akshay Krishnamurthy, Nan Jiang et al.
PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach
Lily Weng, Pin-Yu Chen, Lam Nguyen et al.
QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
Kyunghwan Son, Daewoo Kim, Wan Ju Kang et al.
Quantifying Generalization in Reinforcement Learning
Karl Cobbe, Oleg Klimov, Chris Hesse et al.
Quantile Stein Variational Gradient Descent for Batch Bayesian Optimization
Chengyue Gong, Jian Peng, Qiang Liu
Rademacher Complexity for Adversarially Robust Generalization
Dong Yin, Ramchandran Kannan, Peter Bartlett
RaFM: Rank-Aware Factorization Machines
Xiaoshuang Chen, Yin Zheng, Jiaxing Wang et al.
Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation
Ruohan Wang, Carlo Ciliberto, Pierluigi Vito Amadori et al.
Random Function Priors for Correlation Modeling
Aonan Zhang, John Paisley
Random Matrix Improved Covariance Estimation for a Large Class of Metrics
Malik Tiomoko, Romain Couillet, Florent Bouchard et al.
Random Shuffling Beats SGD after Finite Epochs
Jeff Haochen, Suvrit Sra
Random Walks on Hypergraphs with Edge-Dependent Vertex Weights
Uthsav Chitra, Benjamin Raphael
Rao-Blackwellized Stochastic Gradients for Discrete Distributions
Runjing Liu, Jeffrey Regier, Nilesh Tripuraneni et al.
Rate Distortion For Model Compression:From Theory To Practice
Weihao Gao, Yu-Han Liu, Chong Wang et al.
Rates of Convergence for Sparse Variational Gaussian Process Regression
David Burt, Carl Edward Rasmussen, Mark Van Der Wilk
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces
Philipp Becker, Harit Pandya, Gregor Gebhardt et al.
Recursive Sketches for Modular Deep Learning
Badih Ghazi, Rina Panigrahy, Joshua Wang
Refined Complexity of PCA with Outliers
Kirill Simonov, Fedor Fomin, Petr Golovach et al.
Regret Circuits: Composability of Regret Minimizers
Gabriele Farina, Christian Kroer, Tuomas Sandholm
Regularization in directable environments with application to Tetris
Jan Malte Lichtenberg, Özgür Şimşek
Rehashing Kernel Evaluation in High Dimensions
Paris Siminelakis, Kexin Rong, Peter Bailis et al.
Reinforcement Learning in Configurable Continuous Environments
Alberto Maria Metelli, Emanuele Ghelfi, Marcello Restelli
Relational Pooling for Graph Representations
Ryan Murphy, Balasubramaniam Srinivasan, Vinayak Rao et al.
Remember and Forget for Experience Replay
Guido Novati, Petros Koumoutsakos