Statistical Learning

Distributed Learning of Finite Gaussian Mixtures JMLR 2022 Distributed NLI: Learning to Predict Human Opinion Distributions for Language Reasoning ACL 2022 Distribution-Based Measures of Surprise for Creative Language: Experiments with Humor and Metaphor EMNLP 2022 Distribution Regression with Sliced Wasserstein Kernels ICML 2022 DIVA: Dataset Derivative of a Learning Task ICLR 2022 DNA: Domain Generalization with Diversified Neural Averaging ICML 2022 Does the Data Induce Capacity Control in Deep Learning? ICML 2022 Domain Adaptation meets Individual Fairness. And they get along. NeurIPS 2022 Domain-Lifted Sampling for Universal Two-Variable Logic and Extensions AAAI 2022 DoubleML - An Object-Oriented Implementation of Double Machine Learning in Python JMLR 2022 Double Spike Dirichlet Priors for Structured Weighting JMLR 2022 Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning ICML 2022 DP-PCA: Statistically Optimal and Differentially Private PCA NeurIPS 2022 DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals ICLR 2022 Efficient Aggregated Kernel Tests using Incomplete U-statistics NeurIPS 2022 Efficient and Differentiable Conformal Prediction with General Function Classes ICLR 2022 Efficient and passive learning of networked dynamical systems driven by non-white exogenous inputs AISTATS 2022 Efficient interventional distribution learning in the PAC framework AISTATS 2022 Empirical Risk Minimization under Random Censorship JMLR 2022 EM’s Convergence in Gaussian Latent Tree Models COLT 2022 Entropy Regularized Optimal Transport Independence Criterion AISTATS 2022 Entrywise Recovery Guarantees for Sparse PCA via Sparsistent Algorithms AISTATS 2022 Error-Based Knockoffs Inference for Controlled Feature Selection AAAI 2022 Estimating and Explaining Model Performance When Both Covariates and Labels Shift NeurIPS 2022 Estimating Density Models with Truncation Boundaries using Score Matching JMLR 2022