Papers
A Simple Reward-free Approach to Constrained Reinforcement Learning
Sobhan Miryoosefi, Chi Jin
A Simple Unified Framework for High Dimensional Bandit Problems
Wenjie Li, Adarsh Barik, Jean Honorio
A Simple yet Universal Strategy for Online Convex Optimization
Lijun Zhang, Guanghui Wang, Jinfeng Yi et al.
Asking for Knowledge (AFK): Training RL Agents to Query External Knowledge Using Language
Iou-Jen Liu, Xingdi Yuan, Marc-Alexandre Côté et al.
A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning
Archit Sharma, Rehaan Ahmad, Chelsea Finn
A Statistical Manifold Framework for Point Cloud Data
Yonghyeon Lee, Seungyeon Kim, Jinwon Choi et al.
A Stochastic Multi-Rate Control Framework For Modeling Distributed Optimization Algorithms
Xinwei Zhang, Mingyi Hong, Sairaj Dhople et al.
A Study of Face Obfuscation in ImageNet
Kaiyu Yang, Jacqueline H. Yau, Li Fei-Fei et al.
A Study on the Ramanujan Graph Property of Winning Lottery Tickets
Bithika Pal, Arindam Biswas, Sudeshna Kolay et al.
Asymptotically-Optimal Gaussian Bandits with Side Observations
Alexia Atsidakou, Orestis Papadigenopoulos, Constantine Caramanis et al.
A Temporal-Difference Approach to Policy Gradient Estimation
Samuele Tosatto, Andrew Patterson, Martha White et al.
A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization
Renzhe Xu, Xingxuan Zhang, Zheyan Shen et al.
A Theoretical Comparison of Graph Neural Network Extensions
Pál András Papp, Roger Wattenhofer
A Tighter Analysis of Spectral Clustering, and Beyond
Peter Macgregor, He Sun
A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources
Xiaoqing Tan, Chung-Chou H. Chang, Ling Zhou et al.
Attentional Meta-learners for Few-shot Polythetic Classification
Ben J Day, Ramon Viñas Torné, Nikola Simidjievski et al.
Augment with Care: Contrastive Learning for Combinatorial Problems
Haonan Duan, Pashootan Vaezipoor, Max B Paulus et al.
A Unified View on PAC-Bayes Bounds for Meta-Learning
Arezou Rezazadeh
A Unified Weight Initialization Paradigm for Tensorial Convolutional Neural Networks
Yu Pan, Zeyong Su, Ao Liu et al.
AutoIP: A United Framework to Integrate Physics into Gaussian Processes
Da Long, Zheng Wang, Aditi Krishnapriyan et al.
AutoSNN: Towards Energy-Efficient Spiking Neural Networks
Byunggook Na, Jisoo Mok, Seongsik Park et al.
Auxiliary Learning with Joint Task and Data Scheduling
Hong Chen, Xin Wang, Chaoyu Guan et al.
BabelTower: Learning to Auto-parallelized Program Translation
Yuanbo Wen, Qi Guo, Qiang Fu et al.
Balancing Discriminability and Transferability for Source-Free Domain Adaptation
Jogendra Nath Kundu, Akshay R Kulkarni, Suvaansh Bhambri et al.