sparse regression

Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers NeurIPS 2021 Fair Sparse Regression with Clustering: An Invex Relaxation for a Combinatorial Problem NeurIPS 2021 Fast Projection onto the Capped Simplex with Applications to Sparse Regression in Bioinformatics NeurIPS 2021 Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings ICML 2021 High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation AISTATS 2021 Implicit Sparse Regularization: The Impact of Depth and Early Stopping NeurIPS 2021 Optimal Feedback Law Recovery by Gradient-Augmented Sparse Polynomial Regression JMLR 2021 Principal Component Hierarchy for Sparse Quadratic Programs ICML 2021 Simultaneous Change Point Inference and Structure Recovery for High Dimensional Gaussian Graphical Models JMLR 2021 Sparse Tensor Additive Regression JMLR 2021 Sparsity-Agnostic Lasso Bandit ICML 2021 Stability and Risk Bounds of Iterative Hard Thresholding AISTATS 2021 The Sample Complexity of Meta Sparse Regression AISTATS 2021 Bayesian Model Selection with Graph Structured Sparsity JMLR 2020 EiGLasso: Scalable Estimation of Cartesian Product of Sparse Inverse Covariance Matrices UAI 2020 Empirical Priors for Prediction in Sparse High-dimensional Linear Regression JMLR 2020 Fast OSCAR and OWL Regression via Safe Screening Rules ICML 2020 High Dimensional Robust Sparse Regression AISTATS 2020 Implicit differentiation of Lasso-type models for hyperparameter optimization ICML 2020 Reducibility and Statistical-Computational Gaps from Secret Leakage COLT 2020 Robust Low-Rank Discovery of Data-Driven Partial Differential Equations AAAI 2020 Sparse Hilbert-Schmidt Independence Criterion Regression AISTATS 2020 Sparse Symplectically Integrated Neural Networks NeurIPS 2020 Spike and slab variational Bayes for high dimensional logistic regression NeurIPS 2020 Structured Linear Contextual Bandits: A Sharp and Geometric Smoothed Analysis ICML 2020