learning theory

On the Vulnerability of Fairness Constrained Learning to Malicious Noise AISTATS 2024 On Tractable Φ-Equilibria in Non-Concave Games NeurIPS 2024 Open Problem: Can Local Regularization Learn All Multiclass Problems? COLT 2024 Open problem: Direct Sums in Learning Theory COLT 2024 Optimal Hypothesis Selection in (Almost) Linear Time NeurIPS 2024 Optimal Parallelization of Boosting NeurIPS 2024 Optimal Sample Complexity for Average Reward Markov Decision Processes ICLR 2024 Optimal Sample Complexity of Contrastive Learning ICLR 2024 PAC-Bayes-Chernoff bounds for unbounded losses NeurIPS 2024 Provable Advantage in Quantum PAC Learning COLT 2024 Provable Benefits of Complex Parameterizations for Structured State Space Models NeurIPS 2024 Provable Tempered Overfitting of Minimal Nets and Typical Nets NeurIPS 2024 Quadratic models for understanding catapult dynamics of neural networks ICLR 2024 Realizable H-Consistent and Bayes-Consistent Loss Functions for Learning to Defer NeurIPS 2024 Recursive PAC-Bayes: A Frequentist Approach to Sequential Prior Updates with No Information Loss NeurIPS 2024 Replicability in Learning: Geometric Partitions and KKM-Sperner Lemma NeurIPS 2024 Rethinking Information-theoretic Generalization: Loss Entropy Induced PAC Bounds ICLR 2024 Rethinking the Effectiveness of Graph Classification Datasets in Benchmarks for Assessing GNNs IJCAI 2024 Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models NeurIPS 2024 Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data ICLR 2024 Simplicity Bias in Overparameterized Machine Learning AAAI 2024 Smoothed Analysis for Learning Concepts with Low Intrinsic Dimension COLT 2024 Smoothed Online Classification can be Harder than Batch Classification NeurIPS 2024 Stability and L2-penalty in Model Averaging JMLR 2024 Testably Learning Polynomial Threshold Functions NeurIPS 2024