Learning Theory

Demystifying Disagreement-on-the-Line in High Dimensions ICML 2023 Detection-Recovery and Detection-Refutation Gaps via Reductions from Planted Clique COLT 2023 Deterministic equivalent and error universality of deep random features learning ICML 2023 Differentiable Tree Operations Promote Compositional Generalization ICML 2023 Dimension Reduction in Contextual Online Learning via Nonparametric Variable Selection JMLR 2023 Discovering Language Model Behaviors with Model-Written Evaluations ACL 2023 Discrete-Smoothness in Online Algorithms with Predictions NeurIPS 2023 Distribution Learnability and Robustness NeurIPS 2023 Do Deep Neural Networks Capture Compositionality in Arithmetic Reasoning? EACL 2023 Does a Neural Network Really Encode Symbolic Concepts? ICML 2023 Does Continual Learning Meet Compositionality? New Benchmarks and An Evaluation Framework NeurIPS 2023 Does It Pay to Optimize AUC? AAAI 2023 Does Momentum Help in Stochastic Optimization? A Sample Complexity Analysis. UAI 2023 Does Sparsity Help in Learning Misspecified Linear Bandits? ICML 2023 Do Machine Learning Models Learn Statistical Rules Inferred from Data? ICML 2023 Don’t blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy NeurIPS 2023 Double Doubly Robust Thompson Sampling for Generalized Linear Contextual Bandits AAAI 2023 Dropout Training is Distributionally Robust Optimal JMLR 2023 Dual Algorithmic Reasoning ICLR 2023 Dynamical Linear Bandits ICML 2023 Dynamic Regret of Adversarial Linear Mixture MDPs NeurIPS 2023 Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories ICML 2023 Effects of Human Adversarial and Affable Samples on BERT Generalization EMNLP 2023 Efficient Algorithms for Regret Minimization in Billboard Advertisement (Student Abstract) AAAI 2023 Efficient Algorithms for Sparse Moment Problems without Separation COLT 2023