Statistical Learning

The Reliability of OKRidge Method in Solving Sparse Ridge Regression Problems NeurIPS 2024 The sample complexity of ERMs in stochastic convex optimization AISTATS 2024 The Sample Complexity of Gradient Descent in Stochastic Convex Optimization NeurIPS 2024 The sample complexity of multi-distribution learning COLT 2024 The Sample Complexity of Simple Binary Hypothesis Testing COLT 2024 Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance JMLR 2024 Tight Bounds for Local Glivenko-Cantelli ALT 2024 Tight Rates in Supervised Outlier Transfer Learning ICLR 2024 Tolerant Algorithms for Learning with Arbitrary Covariate Shift NeurIPS 2024 Top-K ranking with a monotone adversary COLT 2024 Toward Conditional Distribution Calibration in Survival Prediction NeurIPS 2024 Towards a Similarity-adjusted Surprisal Theory EMNLP 2024 Towards a statistical theory of data selection under weak supervision ICLR 2024 Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts AISTATS 2024 Towards Costless Model Selection in Contextual Bandits: A Bias-Variance Perspective AISTATS 2024 Towards Estimating Bounds on the Effect of Policies under Unobserved Confounding NeurIPS 2024 Towards Exact Computation of Inductive Bias IJCAI 2024 Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox NeurIPS 2024 Towards More Robust NLP System Evaluation: Handling Missing Scores in Benchmarks EMNLP 2024 Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm JMLR 2024 Towards Safe Policy Learning under Partial Identifiability: A Causal Approach AAAI 2024 Towards the Fundamental Limits of Knowledge Transfer over Finite Domains ICLR 2024 Trading Place for Space: Increasing Location Resolution Reduces Contextual Capacity in Hippocampal Codes NeurIPS 2024 Training Unbiased Diffusion Models From Biased Dataset ICLR 2024 Transductive conformal inference with adaptive scores AISTATS 2024