Theory

Regularizing Towards Soft Equivariance Under Mixed Symmetries ICML 2023 Reinforcement Learning for Joint Optimization of Multiple Rewards JMLR 2023 Relational Debugging --- Pinpointing Root Causes of Performance Problems OSDI 2023 Replicability in Reinforcement Learning NeurIPS 2023 Replicable Reinforcement Learning NeurIPS 2023 Representational Strengths and Limitations of Transformers NeurIPS 2023 Reproducibility in NLP: What Have We Learned from the Checklist? ACL 2023 Residual Alignment: Uncovering the Mechanisms of Residual Networks NeurIPS 2023 Residual-based error bound for physics-informed neural networks UAI 2023 Rethinking Backdoor Attacks ICML 2023 Rethinking the Expressive Power of GNNs via Graph Biconnectivity ICLR 2023 Revisiting Dependency Length and Intervener Complexity Minimisation on a Parallel Corpus in 35 Languages EACL 2023 Revisiting minimum description length complexity in overparameterized models JMLR 2023 Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature ICML 2023 REVISITING PRUNING AT INITIALIZATION THROUGH THE LENS OF RAMANUJAN GRAPH ICLR 2023 Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective NeurIPS 2023 Revisiting the Assumption of Latent Separability for Backdoor Defenses ICLR 2023 Reward Poisoning Attacks on Offline Multi-Agent Reinforcement Learning AAAI 2023 Ridges, Neural Networks, and the Radon Transform JMLR 2023 Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds NeurIPS 2023 Riemannian stochastic optimization methods avoid strict saddle points NeurIPS 2023 Risk Bounds on Aleatoric Uncertainty Recovery AISTATS 2023 Robust Data Valuation with Weighted Banzhaf Values NeurIPS 2023 Robust Methods for High-Dimensional Linear Learning JMLR 2023 Robust Neuro-Symbolic Goal and Plan Recognition AAAI 2023