Papers
Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences
Daniel Brown, Russell Coleman, Ravi Srinivasan et al.
Safe Reinforcement Learning in Constrained Markov Decision Processes
Akifumi Wachi, Yanan Sui
Safe screening rules for L0-regression from Perspective Relaxations
Alper Atamturk, Andres Gomez
Sample Amplification: Increasing Dataset Size even when Learning is Impossible
Brian Axelrod, Shivam Garg, Vatsal Sharan et al.
Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors
Zhaoqiang Liu, Selwyn Gomes, Avtansh Tiwari et al.
Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning
Aleksei Petrenko, Zhehui Huang, Tushar Kumar et al.
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning
Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri et al.
Scalable and Efficient Comparison-based Search without Features
Daniyar Chumbalov, Lucas Maystre, Matthias Grossglauser
Scalable Deep Generative Modeling for Sparse Graphs
Hanjun Dai, Azade Nazi, Yujia Li et al.
Scalable Differentiable Physics for Learning and Control
Yi-Ling Qiao, Junbang Liang, Vladlen Koltun et al.
Scalable Differential Privacy with Certified Robustness in Adversarial Learning
Hai Phan, My T. Thai, Han Hu et al.
Scalable Exact Inference in Multi-Output Gaussian Processes
Wessel Bruinsma, Eric Perim, William Tebbutt et al.
Scalable Gaussian Process Separation for Kernels with a Non-Stationary Phase
Jan Graßhoff, Alexandra Jankowski, Philipp Rostalski
Scalable Identification of Partially Observed Systems with Certainty-Equivalent EM
Kunal Menda, Jean De Becdelievre, Jayesh Gupta et al.
Scalable Nearest Neighbor Search for Optimal Transport
Arturs Backurs, Yihe Dong, Piotr Indyk et al.
Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing
Zhe Zeng, Paolo Morettin, Fanqi Yan et al.
Schatten Norms in Matrix Streams: Hello Sparsity, Goodbye Dimension
Vladimir Braverman, Robert Krauthgamer, Aditya Krishnan et al.
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates
Lingkai Kong, Jimeng Sun, Chao Zhang
Searching to Exploit Memorization Effect in Learning with Noisy Labels
Quanming Yao, Hansi Yang, Bo Han et al.
Second-Order Provable Defenses against Adversarial Attacks
Sahil Singla, Soheil Feizi
Selective Dyna-Style Planning Under Limited Model Capacity
Zaheer Abbas, Samuel Sokota, Erin Talvitie et al.
Self-Attentive Associative Memory
Hung Le, Truyen Tran, Svetha Venkatesh
Self-Attentive Hawkes Process
Qiang Zhang, Aldo Lipani, Omer Kirnap et al.
Self-Concordant Analysis of Frank-Wolfe Algorithms
Pavel Dvurechensky, Petr Ostroukhov, Kamil Safin et al.
Self-Modulating Nonparametric Event-Tensor Factorization
Zheng Wang, Xinqi Chu, Shandian Zhe