Learning Theory

Improved Regret in Stochastic Decision-Theoretic Online Learning under Differential Privacy ALT 2026 Improved Replicable Boosting with Majority-of-Majorities ALT 2026 Improving Exact Algorithm for Pseudo Boolean Optimization with Two New Phase Selection Heuristics AAAI 2026 Inference Scaling Law for Retrieval Augmented Generation AAAI 2026 Information-computation gaps in quantum learning via low-degree likelihood COLT 2026 Invited Open Problem: Does Differential Privacy Make PAC Learning Much Harder? COLT 2026 Invited Open Problem: Is the Power of Deep Learning over Linear Models Inherently Distribution Dependent? COLT 2026 Invited Open Problem: Online Optimization of Piecewise-Lipschitz Functions with Applications to Data-Driven Algorithm Design COLT 2026 Is Multi-Distribution Learning as Easy as PAC Learning: Sharp Rates with Bounded Label Noise COLT 2026 Language Identification with Succinct Machine-Independent Traces COLT 2026 Learning-Augmented Ski Rental with Discrete Distribution: A Bayesian Approach AAAI 2026 Learning Conditional Averages COLT 2026 Learning Decision-Sufficient Representations for Linear Optimization COLT 2026 Learning depth-3 circuits via quantum agnostic boosting COLT 2026 Learning DFAs from Positive Examples Only via Word Counting AAAI 2026 Learning from Answer Sets via Single-Shot Disjunctive ASP Encoding AAAI 2026 Learning from Synthetic Data: Limitations of ERM ALT 2026 Learning Ising Models from Evolutions (Extended Abstract) COLT 2026 Learning Protein–Ligand Binding in Hyperbolic Space AAAI 2026 Learning Subgroups with Maximum Treatment Effects Without Causal Heuristics AAAI 2026 Learning with Monotone Adversarial Corruptions ALT 2026 Learning with Simulators: No Regret in a Computationally Bounded World COLT 2026 Leveraging Similarities in Multi-Armed Bandits COLT 2026 Lexical Popularity: Quantifying the Impact of Pre-training for LLM Performance EACL 2026 Limitations of SGD for Multi-Index Models Beyond Statistical Queries COLT 2026