Statistics

Generalizing Nonlinear ICA Beyond Structural Sparsity NeurIPS 2023 Geodesically convex M-estimation in metric spaces COLT 2023 High-dimensional Asymptotics of Denoising Autoencoders NeurIPS 2023 High-dimensional Location Estimation via Norm Concentration for Subgamma Vectors ICML 2023 H-Likelihood Approach to Deep Neural Networks with Temporal-Spatial Random Effects for High-Cardinality Categorical Features ICML 2023 Huber-robust confidence sequences AISTATS 2023 Hypothesis Selection with Memory Constraints NeurIPS 2023 Identifying Stable Sections for Formant Frequency Extraction of French Nasal Vowels Based on Difference Thresholds Interspeech 2023 Improving multiple-try Metropolis with local balancing JMLR 2023 Increasing effect sizes of pairwise conditional independence tests between random vectors UAI 2023 Inference for Gaussian Processes with Matern Covariogram on Compact Riemannian Manifolds JMLR 2023 Inference on Strongly Identified Functionals of Weakly Identified Functions COLT 2023 Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise COLT 2023 Integer Subspace Differential Privacy AAAI 2023 Interaction Measures, Partition Lattices and Kernel Tests for High-Order Interactions NeurIPS 2023 Kernel-Based Tests for Likelihood-Free Hypothesis Testing NeurIPS 2023 Kernelized Cumulants: Beyond Kernel Mean Embeddings NeurIPS 2023 Kernel Sufficient Dimension Reduction and Variable Selection for Compositional Data via Amalgamation ICML 2023 K-Nearest-Neighbor Local Sampling Based Conditional Independence Testing NeurIPS 2023 Langevin Quasi-Monte Carlo NeurIPS 2023 Learning a Deep Color Difference Metric for Photographic Images CVPR 2023 Learning Exponential Families from Truncated Samples NeurIPS 2023 Learning Mixtures of Gaussians with Censored Data ICML 2023 Learning Nonlinear Causal Effect via Kernel Anchor Regression UAI 2023 Linear optimal partial transport embedding ICML 2023