Papers
Optimal Continual Learning has Perfect Memory and is NP-hard
Jeremias Knoblauch, Hisham Husain, Tom Diethe
Optimal Differential Privacy Composition for Exponential Mechanisms
Jinshuo Dong, David Durfee, Ryan Rogers
Optimal Estimator for Unlabeled Linear Regression
Hang Zhang, Ping Li
Optimally Solving Two-Agent Decentralized POMDPs Under One-Sided Information Sharing
Yuxuan Xie, Jilles Dibangoye, Olivier Buffet
Optimal Randomized First-Order Methods for Least-Squares Problems
Jonathan Lacotte, Mert Pilanci
Optimal Robust Learning of Discrete Distributions from Batches
Ayush Jain, Alon Orlitsky
Optimal Sequential Maximization: One Interview is Enough!
Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati
Optimal transport mapping via input convex neural networks
Ashok Makkuva, Amirhossein Taghvaei, Sewoong Oh et al.
Optimistic Bounds for Multi-output Learning
Henry Reeve, Ata Kaban
Optimistic Policy Optimization with Bandit Feedback
Lior Shani, Yonathan Efroni, Aviv Rosenberg et al.
Optimization and Analysis of the pAp@k Metric for Recommender Systems
Gaurush Hiranandani, Warut Vijitbenjaronk, Sanmi Koyejo et al.
Optimization from Structured Samples for Coverage Functions
Wei Chen, Xiaoming Sun, Jialin Zhang et al.
Optimization Theory for ReLU Neural Networks Trained with Normalization Layers
Yonatan Dukler, Quanquan Gu, Guido Montufar
Optimizer Benchmarking Needs to Account for Hyperparameter Tuning
Prabhu Teja Sivaprasad, Florian Mai, Thijs Vogels et al.
Optimizing Black-box Metrics with Adaptive Surrogates
Qijia Jiang, Olaoluwa Adigun, Harikrishna Narasimhan et al.
Optimizing Data Usage via Differentiable Rewards
Xinyi Wang, Hieu Pham, Paul Michel et al.
Optimizing Dynamic Structures with Bayesian Generative Search
Minh Hoang, Carleton Kingsford
Optimizing for the Future in Non-Stationary MDPs
Yash Chandak, Georgios Theocharous, Shiv Shankar et al.
Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach
Martin Mladenov, Elliot Creager, Omer Ben-Porat et al.
Option Discovery in the Absence of Rewards with Manifold Analysis
Amitay Bar, Ronen Talmon, Ron Meir
OPtions as REsponses: Grounding behavioural hierarchies in multi-agent reinforcement learning
Alexander Vezhnevets, Yuhuai Wu, Maria Eckstein et al.
Oracle Efficient Private Non-Convex Optimization
Seth Neel, Aaron Roth, Giuseppe Vietri et al.
Ordinal Non-negative Matrix Factorization for Recommendation
Olivier Gouvert, Thomas Oberlin, Cédric Févotte
Orthogonalized SGD and Nested Architectures for Anytime Neural Networks
Chengcheng Wan, Henry Hoffmann, Shan Lu et al.