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1219 directly classified papers

Papers per year

Papers

On the Estimation of Derivatives Using Plug-in Kernel Ridge Regression Estimators JMLR 2023
On Computing Pairwise Statistics with Local Differential Privacy NIPS 2023
Risk-limiting financial audits via weighted sampling without replacement UAI 2023
Learning Nonlinear Causal Effect via Kernel Anchor Regression UAI 2023
A Measure-Theoretic Axiomatisation of Causality NIPS 2023
Feature Adaptation for Sparse Linear Regression NIPS 2023
Statistical Limits of Adaptive Linear Models: Low-Dimensional Estimation and Inference NIPS 2023
Time-uniform confidence bands for the CDF under nonstationarity NIPS 2023
Minimax Nonparametric Two-Sample Test under Adversarial Losses AISTATS 2023
Optimality in Mean Estimation: Beyond Worst-Case, Beyond Sub-Gaussian, and Beyond $1+\alpha$ Moments NIPS 2023
Kernelized Cumulants: Beyond Kernel Mean Embeddings NIPS 2023
Efficient preconditioned stochastic gradient descent for estimation in latent variable models ICML 2023
Integer Subspace Differential Privacy AAAI 2023
Mean Estimation of Truncated Mixtures of Two Gaussians: A Gradient Based Approach AAAI 2023
Two Sample Testing in High Dimension via Maximum Mean Discrepancy JMLR 2023
Semi-Dual Unbalanced Quadratic Optimal Transport: fast statistical rates and convergent algorithm. ICML 2023
Adaptive Estimation of Graphical Models under Total Positivity ICML 2023
Minimax-Optimal Location Estimation NIPS 2023
K-Nearest-Neighbor Local Sampling Based Conditional Independence Testing NIPS 2023
Minimax Optimal Rate for Parameter Estimation in Multivariate Deviated Models NIPS 2023
A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm NIPS 2023
Discovery of Single Independent Latent Variable NIPS 2022
RUMs from Head-to-Head Contests ICML 2022
Nyström Kernel Mean Embeddings ICML 2022
Kernel Partial Correlation Coefficient --- a Measure of Conditional Dependence JMLR 2022