pac learning

Actively Learning Halfspaces without Synthetic Data COLT 2026 Concept Sketching for Description Logics UAI 2026 Invited Open Problem: Does Differential Privacy Make PAC Learning Much Harder? COLT 2026 Is Multi-Distribution Learning as Easy as PAC Learning: Sharp Rates with Bounded Label Noise COLT 2026 Learning Conditional Averages COLT 2026 Learning Decision-Sufficient Representations for Linear Optimization COLT 2026 Learning from Synthetic Data: Limitations of ERM ALT 2026 No Scale Sensitive Dimension for Distribution Learning ALT 2026 On the Hardness of Learning Regular Expressions ALT 2026 Relatively Smart: A New Approach for Instance-Optimal Learning COLT 2026 When Can We Learn from Noisy Logical Data? Parameterized Complexity of Approximate Concept Fitting in Description Logics UAI 2026 Active Bipartite Ranking with Smooth Posterior Distributions AISTATS 2025 A Distributional-Lifting Theorem for PAC Learning COLT 2025 Distributional Adversarial Loss AISTATS 2025 Distribution-Specific Agnostic Conditional Classification With Halfspaces ICLR 2025 Do PAC-Learners Learn the Marginal Distribution? ALT 2025 Efficient Optimal PAC Learning ALT 2025 Efficient PAC Learning of Halfspaces with Constant Malicious Noise Rate ALT 2025 Extracting PAC Decision Trees from Black Box Binary Classifiers: The Gender Bias Study Case on BERT-based Language Models AAAI 2025 Is Transductive Learning Equivalent to PAC Learning? ALT 2025 Probably approximately correct high-dimensional causal effect estimation given a valid adjustment set CLeaR 2025 Strategic Classification With Externalities ICLR 2025 A Near-optimal Algorithm for Learning Margin Halfspaces with Massart Noise NeurIPS 2024 A PAC Learning Algorithm for LTL and Omega-Regular Objectives in MDPs AAAI 2024 Credit Attribution and Stable Compression NeurIPS 2024