Papers
Reward-Weighted Regression Converges to a Global Optimum
Miroslav Štrupl, Francesco Faccio, Dylan R. Ashley et al.
ReX: An Efficient Approach to Reducing Memory Cost in Image Classification
Xuwei Qian, Renlong Hang, Qingshan Liu
RID-Noise: Towards Robust Inverse Design under Noisy Environments
Jia-Qi Yang, Ke-Bin Fan, Hao Ma et al.
Risk-Aware Stochastic Shortest Path
Tobias Meggendorfer
Robust Action Gap Increasing with Clipped Advantage Learning
Zhe Zhang, Yaozhong Gan, Xiaoyang Tan
Robust Adversarial Reinforcement Learning with Dissipation Inequation Constraint
Peng Zhai, Jie Luo, Zhiyan Dong et al.
Robust and Resource-Efficient Data-Free Knowledge Distillation by Generative Pseudo Replay
Kuluhan Binici, Shivam Aggarwal, Nam Trung Pham et al.
Robust Depth Completion with Uncertainty-Driven Loss Functions
Yufan Zhu, Weisheng Dong, Leida Li et al.
Robust Graph-Based Multi-View Clustering
Weixuan Liang, Xinwang Liu, Sihang Zhou et al.
Robust Heterogeneous Graph Neural Networks against Adversarial Attacks
Mengmei Zhang, Xiao Wang, Meiqi Zhu et al.
Robustification of Online Graph Exploration Methods
Franziska Eberle, Alexander Lindermayr, Nicole Megow et al.
Robust Optimal Classification Trees against Adversarial Examples
Daniël Vos, Sicco Verwer
Robust Tests in Online Decision-Making
Gi-Soo Kim, Jane P Kim, Hyun-Joon Yang
Role of Human-AI Interaction in Selective Prediction
Elizabeth Bondi, Raphael Koster, Hannah Sheahan et al.
RRL: Regional Rotate Layer in Convolutional Neural Networks
Zongbo Hao, Tao Zhang, Mingwang Chen et al.
Rushing and Strolling among Answer Sets – Navigation Made Easy
Johannes Klaus Fichte, Sarah Alice Gaggl, Dominik Rusovac
Safe Distillation Box
Jingwen Ye, Yining Mao, Jie Song et al.
Safe Online Convex Optimization with Unknown Linear Safety Constraints
Sapana Chaudhary, Dileep Kalathil
Safe Subgame Resolving for Extensive Form Correlated Equilibrium
Chun Kai Ling, Fei Fang
SAIL: Self-Augmented Graph Contrastive Learning
Lu Yu, Shichao Pei, Lizhong Ding et al.
Saliency Grafting: Innocuous Attribution-Guided Mixup with Calibrated Label Mixing
Joonhyung Park, June Yong Yang, Jinwoo Shin et al.
Same State, Different Task: Continual Reinforcement Learning without Interference
Samuel Kessler, Jack Parker-Holder, Philip Ball et al.
Sample Average Approximation for Stochastic Optimization with Dependent Data: Performance Guarantees and Tractability
Yafei Wang, Bo Pan, Wei Tu et al.
Sample-Efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs
Siow Meng Low, Akshat Kumar, Scott Sanner