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Statistical Learning

4,117 papers

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Papers

Minimax Instrumental Variable Regression and $L_2$ Convergence Guarantees without Identification or Closedness COLT 2023
Detection-Recovery Gap for Planted Dense Cycles COLT 2023
Tight Bounds on the Hardness of Learning Simple Nonparametric Mixtures COLT 2023
Algorithmic Gaussianization through Sketching: Converting Data into Sub-gaussian Random Designs COLT 2023
Simple Binary Hypothesis Testing under Local Differential Privacy and Communication Constraints COLT 2023
Efficient Algorithms for Sparse Moment Problems without Separation COLT 2023
Near Optimal Heteroscedastic Regression with Symbiotic Learning COLT 2023
A High-dimensional Convergence Theorem for U-statistics with Applications to Kernel-based Testing COLT 2023
Entropic characterization of optimal rates for learning Gaussian mixtures COLT 2023
Sparse PCA Beyond Covariance Thresholding COLT 2023
Finite-Sample Symmetric Mean Estimation with Fisher Information Rate COLT 2023
Generalization Guarantees via Algorithm-dependent Rademacher Complexity COLT 2023
Shortest Program Interpolation Learning COLT 2023
PAC Verification of Statistical Algorithms COLT 2023
Empirical Bayes via ERM and Rademacher complexities: the Poisson model COLT 2023
Minimax optimal testing by classification COLT 2023
The Aggregation–Heterogeneity Trade-off in Federated Learning COLT 2023
Universal Rates for Multiclass Learning COLT 2023
Local Risk Bounds for Statistical Aggregation COLT 2023
Limits of Model Selection under Transfer Learning COLT 2023
Bandit Learnability can be Undecidable COLT 2023
Fine-Grained Distribution-Dependent Learning Curves COLT 2023
Efficient median of means estimator COLT 2023
Open Problem: The Sample Complexity of Multi-Distribution Learning for VC Classes COLT 2023
Leveraging Inter-Rater Agreement for Classification in the Presence of Noisy Labels CVPR 2023