Statistical Learning

Neuron-Enhanced AutoEncoder Matrix Completion and Collaborative Filtering: Theory and Practice ICLR 2024 New Lower Bounds for Testing Monotonicity and Log Concavity of Distributions COLT 2024 Noisy Label Learning with Instance-Dependent Outliers: Identifiability via Crowd Wisdom NeurIPS 2024 Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning NeurIPS 2024 Non-Exchangeable Conformal Risk Control ICLR 2024 Non-parametric classification via expand-and-sparsify representation NeurIPS 2024 Nonparametric Detection of Gerrymandering in Multiparty Plurality Elections IJCAI 2024 Nonparametric Inference under B-bits Quantization JMLR 2024 Non-vacuous Generalization Bounds for Adversarial Risk in Stochastic Neural Networks AISTATS 2024 Nowcasting Temporal Trends Using Indirect Surveys AAAI 2024 Occupancy-based Policy Gradient: Estimation, Convergence, and Optimality NeurIPS 2024 On Comparing Time- and Frequency-Domain Rhythm Measures in Classifying Assamese Dialects Interspeech 2024 On Differentially Private Subspace Estimation in a Distribution-Free Setting NeurIPS 2024 On Differentially Private U Statistics NeurIPS 2024 On Doubly Robust Inference for Double Machine Learning in Semiparametric Regression JMLR 2024 On Efficient and Scalable Computation of the Nonparametric Maximum Likelihood Estimator in Mixture Models JMLR 2024 On Efficient and Statistical Quality Estimation for Data Annotation ACL 2024 Online Consistency of the Nearest Neighbor Rule NeurIPS 2024 Online Distribution Learning with Local Privacy Constraints AISTATS 2024 Online Estimation via Offline Estimation: An Information-Theoretic Framework NeurIPS 2024 On Parameter Estimation in Deviated Gaussian Mixture of Experts AISTATS 2024 On Statistical Learning Theory for Distributional Inputs ICML 2024 On Tail Decay Rate Estimation of Loss Function Distributions JMLR 2024 On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries NeurIPS 2024 On the Computability of Robust PAC Learning COLT 2024