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Statistical Learning

65 directly classified papers

Papers per year

Papers

Conditional Diffusion Models Based Conditional Independence Testing AAAI 2025
Knockoffs Inference for Partially Linear Models with Automatic Structure Discovery AAAI 2025
Breaking the curse of dimensionality in structured density estimation NIPS 2024
Active Classification with Few Queries under Misspecification NIPS 2024
Real-Time Selection Under General Constraints via Predictive Inference NIPS 2024
Nowcasting Temporal Trends Using Indirect Surveys AAAI 2024
On Differentially Private U Statistics NIPS 2024
Online Estimation via Offline Estimation: An Information-Theoretic Framework NIPS 2024
On the Variance, Admissibility, and Stability of Empirical Risk Minimization NIPS 2023
Exact recovery and Bregman hard clustering of node-attributed Stochastic Block Model NIPS 2023
Can semi-supervised learning use all the data effectively? A lower bound perspective NIPS 2023
SQ Lower Bounds for Learning Mixtures of Linear Classifiers NIPS 2023
Nearest-Neighbor Sampling Based Conditional Independence Testing AAAI 2023
Learning Exponential Families from Truncated Samples NIPS 2023
Frustratingly Easy Truth Discovery AAAI 2023
Divide and Conquer Dynamic Programming: An Almost Linear Time Change Point Detection Methodology in High Dimensions ICML 2023
Non-Iterative Recovery From Nonlinear Observations Using Generative Models CVPR 2022
The Complexity of Learning Approval-Based Multiwinner Voting Rules AAAI 2022
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models NIPS 2022
Robust Model Selection and Nearly-Proper Learning for GMMs NIPS 2022
Learning with little mixing NIPS 2022
On the Complexity of Inductively Learning Guarded Clauses AAAI 2022
Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap NIPS 2022
Statistical Undecidability in Linear, Non-Gaussian Causal Models in the Presence of Latent Confounders NIPS 2021
Estimating the Lasso's Effective Noise JMLR 2021