sparse regression

Subset Selection by Pareto Optimization with Recombination AAAI 2020 Support recovery and sup-norm convergence rates for sparse pivotal estimation AISTATS 2020 Adaptive Hard Thresholding for Near-optimal Consistent Robust Regression COLT 2019 An Efficient Two Step Algorithm for High Dimensional Change Point Regression Models Without Grid Search JMLR 2019 Binarsity: a penalization for one-hot encoded features in linear supervised learning JMLR 2019 Conditional Sparse L_p-norm Regression With Optimal Probability AISTATS 2019 Dependent relevance determination for smooth and structured sparse regression JMLR 2019 Doubly-Robust Lasso Bandit NeurIPS 2019 HMLasso: Lasso with High Missing Rate IJCAI 2019 InteractionNN: A Neural Network for Learning Hidden Features in Sparse Prediction IJCAI 2019 Solving the OSCAR and SLOPE Models Using a Semismooth Newton-Based Augmented Lagrangian Method JMLR 2019 Sparse High-Dimensional Isotonic Regression NeurIPS 2019 Sparse Kernel Regression with Coefficient-based ℓ_q-regularization JMLR 2019 Statistical-Computational Tradeoff in Single Index Models NeurIPS 2019 The Impact of Regularization on High-dimensional Logistic Regression NeurIPS 2019 Trimming the ℓ_1 Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning ICML 2019 Accelerated Difference of Convex functions Algorithm and its Application to Sparse Binary Logistic Regression IJCAI 2018 A Constructive Approach to L_0 Penalized Regression JMLR 2018 Bilevel learning of the Group Lasso structure NeurIPS 2018 Boosted Sparse and Low-Rank Tensor Regression NeurIPS 2018 Generalized Concomitant Multi-Task Lasso for Sparse Multimodal Regression AISTATS 2018 Gradient Hard Thresholding Pursuit JMLR 2018 Independently Interpretable Lasso: A New Regularizer for Sparse Regression with Uncorrelated Variables AISTATS 2018 MixLasso: Generalized Mixed Regression via Convex Atomic-Norm Regularization NeurIPS 2018 On Tight Bounds for the Lasso JMLR 2018