Learning Theory

Exploiting Human-AI Dependence for Learning to Defer ICML 2024 Exploring the cloud of feature interaction scores in a Rashomon set ICLR 2024 Exploring the Complexity of Deep Neural Networks through Functional Equivalence ICML 2024 Exploring the Learning Capabilities of Language Models using LEVERWORLDS EMNLP 2024 Exploring the Relationship between In-Context Learning and Instruction Tuning EMNLP 2024 Exploring Transformer Extrapolation AAAI 2024 Exponential Hardness of Optimization from the Locality in Quantum Neural Networks AAAI 2024 Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition JMLR 2024 Expressivity and Generalization: Fragment-Biases for Molecular GNNs ICML 2024 Factored-Reward Bandits with Intermediate Observations ICML 2024 Fair Online Bilateral Trade NeurIPS 2024 FairWire: Fair Graph Generation NeurIPS 2024 Fantastic Generalization Measures are Nowhere to be Found ICLR 2024 Fast Co-Training under Weak Dependence via Stream-Based Active Learning ICML 2024 Fast Dynamic Sampling for Determinantal Point Processes AISTATS 2024 Faster Convergence with MultiWay Preferences AISTATS 2024 Fast Rates for Bandit PAC Multiclass Classification NeurIPS 2024 Fast Rates in Stochastic Online Convex Optimization by Exploiting the Curvature of Feasible Sets NeurIPS 2024 Fat-Shattering Dimension of k-fold Aggregations JMLR 2024 Fault Tolerant ML: Efficient Meta-Aggregation and Synchronous Training ICML 2024 Feasible Q-Learning for Average Reward Reinforcement Learning AISTATS 2024 Feature Contamination: Neural Networks Learn Uncorrelated Features and Fail to Generalize ICML 2024 Feature emergence via margin maximization: case studies in algebraic tasks ICLR 2024 Federated Q-Learning: Linear Regret Speedup with Low Communication Cost ICLR 2024 Federated X-armed Bandit AAAI 2024