concept class

Boosting with List-Decodable Codes COLT 2026 Invited Open Problem: Does Differential Privacy Make PAC Learning Much Harder? COLT 2026 Learning Conditional Averages COLT 2026 Lower Bounds for Greedy Teaching Set Constructions COLT 2025 A Theory of Interpretable Approximations COLT 2024 A Theory of Optimistically Universal Online Learnability for General Concept Classes NeurIPS 2024 Dual VC Dimension Obstructs Sample Compression by Embeddings COLT 2024 Improved Sample Complexity for Multiclass PAC Learning NeurIPS 2024 Learning from Snapshots of Discrete and Continuous Data Streams NeurIPS 2024 MAP- and MLE-Based Teaching JMLR 2024 Non-Clashing Teaching Maps for Balls in Graphs COLT 2024 On a Combinatorial Problem Arising in Machine Teaching ICML 2024 Provable Advantage in Quantum PAC Learning COLT 2024 Testably Learning Polynomial Threshold Functions NeurIPS 2024 The Dimension of Self-Directed Learning ALT 2024 Universal Rates for Active Learning NeurIPS 2024 Fine-Grained Distribution-Dependent Learning Curves COLT 2023 On Batch Teaching Without Collusion JMLR 2023 Ticketed Learning–Unlearning Schemes COLT 2023 Tournaments, Johnson Graphs and NC-Teaching ALT 2023 Learning with Distributional Inverters ALT 2022 Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes NeurIPS 2022 Unlabelled Sample Compression Schemes for Intersection-Closed Classes and Extremal Classes NeurIPS 2022 A Theory of Heuristic Learnability COLT 2021 Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games COLT 2021