Papers
Restarting Frank-Wolfe
Thomas Kerdreux, Alexandre d’Aspremont, Sebastian Pokutta
Reversible Jump Probabilistic Programming
David A. Roberts, Marcus Gallagher, Thomas Taimre
Revisiting Adversarial Risk
Arun Sai Suggala, Adarsh Prasad, Vaishnavh Nagarajan et al.
Risk-Averse Stochastic Convex Bandit
Adrian Rivera Cardoso, Huan Xu
Risk-Sensitive Generative Adversarial Imitation Learning
Jonathan Lacotte, Mohammad Ghavamzadeh, Yinlam Chow et al.
Robust descent using smoothed multiplicative noise
Matthew J. Holland
Robust Graph Embedding with Noisy Link Weights
Akifumi Okuno, Hidetoshi Shimodaira
Robust Matrix Completion from Quantized Observations
Jie Shen, Pranjal Awasthi, Ping Li
Robustness Guarantees for Density Clustering
Heinrich Jiang, Jennifer Jang, Ofir Nachum
Rotting bandits are no harder than stochastic ones
Julien Seznec, Andrea Locatelli, Alexandra Carpentier et al.
Safe Convex Learning under Uncertain Constraints
Ilnura Usmanova, Andreas Krause, Maryam Kamgarpour
Sample Complexity of Sinkhorn Divergences
Aude Genevay, Lénaïc Chizat, Francis Bach et al.
Sample Efficient Graph-Based Optimization with Noisy Observations
Thanh Tan Nguyen, Ali Shameli, Yasin Abbasi-Yadkori et al.
Sample-Efficient Imitation Learning via Generative Adversarial Nets
Lionel Blondé, Alexandros Kalousis
Sampling from Non-Log-Concave Distributions via Variance-Reduced Gradient Langevin Dynamics
Difan Zou, Pan Xu, Quanquan Gu
Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers
Marcel Hirt, Petros Dellaportas
Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees
Jonathan H. Huggins, Trevor Campbell, Mikolaj Kasprzak et al.
Scalable High-Order Gaussian Process Regression
Shandian Zhe, Wei Xing, Robert M. Kirby
Scalable Thompson Sampling via Optimal Transport
Ruiyi Zhang, Zheng Wen, Changyou Chen et al.
Semi-Generative Modelling: Covariate-Shift Adaptation with Cause and Effect Features
Julius Kügelgen, Alexander Mey, Marco Loog
Semi-supervised clustering for de-duplication
Shrinu Kushagra, Shai Ben-David, Ihab Ilyas
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows
George Papamakarios, David Sterratt, Iain Murray
Sequential Patient Recruitment and Allocation for Adaptive Clinical Trials
Onur Atan, William R. Zame, Mihaela Schaar
Sharp Analysis of Learning with Discrete Losses
Alex Nowak, Francis Bach, Alessandro Rudi