Papers
Randomization matters How to defend against strong adversarial attacks
Rafael Pinot, Raphael Ettedgui, Geovani Rizk et al.
Randomized Block-Diagonal Preconditioning for Parallel Learning
Celestine Mendler-Dünner, Aurelien Lucchi
Randomized Smoothing of All Shapes and Sizes
Greg Yang, Tony Duan, J. Edward Hu et al.
Randomly Projected Additive Gaussian Processes for Regression
Ian Delbridge, David Bindel, Andrew Gordon Wilson
Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures
Mohamed El Amine Seddik, Cosme Louart, Mohamed Tamaazousti et al.
Rank Aggregation from Pairwise Comparisons in the Presence of Adversarial Corruptions
Arpit Agarwal, Shivani Agarwal, Sanjeev Khanna et al.
Rate-distortion optimization guided autoencoder for isometric embedding in Euclidean latent space
Keizo Kato, Jing Zhou, Tomotake Sasaki et al.
Ready Policy One: World Building Through Active Learning
Philip Ball, Jack Parker-Holder, Aldo Pacchiano et al.
Real-Time Optimisation for Online Learning in Auctions
Lorenzo Croissant, Marc Abeille, Clement Calauzenes
Recht-Re Noncommutative Arithmetic-Geometric Mean Conjecture is False
Zehua Lai, Lek-Heng Lim
Recovery of Sparse Signals from a Mixture of Linear Samples
Soumyabrata Pal, Arya Mazumdar
Recurrent Hierarchical Topic-Guided RNN for Language Generation
Dandan Guo, Bo Chen, Ruiying Lu et al.
Reducing Sampling Error in Batch Temporal Difference Learning
Brahma Pavse, Ishan Durugkar, Josiah Hanna et al.
Refined bounds for algorithm configuration: The knife-edge of dual class approximability
Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik
Regularized Optimal Transport is Ground Cost Adversarial
François-Pierre Paty, Marco Cuturi
Reinforcement Learning for Integer Programming: Learning to Cut
Yunhao Tang, Shipra Agrawal, Yuri Faenza
Reinforcement Learning for Molecular Design Guided by Quantum Mechanics
Gregor Simm, Robert Pinsler, Jose Miguel Hernandez-Lobato
Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism
Wang Chi Cheung, David Simchi-Levi, Ruihao Zhu
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound
Lin Yang, Mengdi Wang
Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows
Rob Cornish, Anthony Caterini, George Deligiannidis et al.
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
Francesco Croce, Matthias Hein
Reliable Fidelity and Diversity Metrics for Generative Models
Muhammad Ferjad Naeem, Seong Joon Oh, Youngjung Uh et al.
Representation Learning via Adversarially-Contrastive Optimal Transport
Anoop Cherian, Shuchin Aeron
Representations for Stable Off-Policy Reinforcement Learning
Dibya Ghosh, Marc G. Bellemare
Representing Unordered Data Using Complex-Weighted Multiset Automata
Justin DeBenedetto, David Chiang