Papers
Robust Asymmetric Learning in POMDPs
Andrew Warrington, Jonathan W Lavington, Adam Scibior et al.
Robust Density Estimation from Batches: The Best Things in Life are (Nearly) Free
Ayush Jain, Alon Orlitsky
Robust Inference for High-Dimensional Linear Models via Residual Randomization
Y. Samuel Wang, Si Kai Lee, Panos Toulis et al.
Robust Learning-Augmented Caching: An Experimental Study
Jakub Chłędowski, Adam Polak, Bartosz Szabucki et al.
Robust Learning for Data Poisoning Attacks
Yunjuan Wang, Poorya Mianjy, Raman Arora
Robust Policy Gradient against Strong Data Corruption
Xuezhou Zhang, Yiding Chen, Xiaojin Zhu et al.
Robust Pure Exploration in Linear Bandits with Limited Budget
Ayya Alieva, Ashok Cutkosky, Abhimanyu Das
Robust Reinforcement Learning using Least Squares Policy Iteration with Provable Performance Guarantees
Kishan Panaganti Badrinath, Dileep Kalathil
Robust Representation Learning via Perceptual Similarity Metrics
Saeid A Taghanaki, Kristy Choi, Amir Hosein Khasahmadi et al.
Robust Testing and Estimation under Manipulation Attacks
Jayadev Acharya, Ziteng Sun, Huanyu Zhang
Robust Unsupervised Learning via L-statistic Minimization
Andreas Maurer, Daniela Angela Parletta, Andrea Paudice et al.
RRL: Resnet as representation for Reinforcement Learning
Rutav M Shah, Vikash Kumar
Run-Sort-ReRun: Escaping Batch Size Limitations in Sliced Wasserstein Generative Models
Jose Lezama, Wei Chen, Qiang Qiu
Safe Reinforcement Learning Using Advantage-Based Intervention
Nolan C Wagener, Byron Boots, Ching-An Cheng
Safe Reinforcement Learning with Linear Function Approximation
Sanae Amani, Christos Thrampoulidis, Lin Yang
SagaNet: A Small Sample Gated Network for Pediatric Cancer Diagnosis
Yuhan Liu, Shiliang Sun
SAINT-ACC: Safety-Aware Intelligent Adaptive Cruise Control for Autonomous Vehicles Using Deep Reinforcement Learning
Lokesh Chandra Das, Myounggyu Won
Sample Complexity of Robust Linear Classification on Separated Data
Robi Bhattacharjee, Somesh Jha, Kamalika Chaudhuri
Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity
Dhruv Malik, Aldo Pacchiano, Vishwak Srinivasan et al.
Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network
Zhibin Duan, Dongsheng Wang, Bo Chen et al.
Scalable Certified Segmentation via Randomized Smoothing
Marc Fischer, Maximilian Baader, Martin Vechev
Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks
Jiaojiao Fan, Amirhossein Taghvaei, Yongxin Chen
Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot
Joel Z Leibo, Edgar A Dueñez-Guzman, Alexander Vezhnevets et al.
Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning
Alexander Immer, Matthias Bauer, Vincent Fortuin et al.