variable selection

Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives JMLR 2021 Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications AISTATS 2021 Nonparametric Variable Screening with Optimal Decision Stumps AISTATS 2021 Optimal Minimax Variable Selection for Large-Scale Matrix Linear Regression Model JMLR 2021 Ordering-Based Causal Discovery with Reinforcement Learning IJCAI 2021 Post-selection inference with HSIC-Lasso ICML 2021 Toward Optimal Solution for the Context-Attentive Bandit Problem IJCAI 2021 Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon AISTATS 2021 A General Large Neighborhood Search Framework for Solving Integer Linear Programs NeurIPS 2020 Aggregation of Multiple Knockoffs ICML 2020 Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee NeurIPS 2020 Guiding CDCL SAT Search via Random Exploration amid Conflict Depression AAAI 2020 Learning Hierarchical Interactions at Scale: A Convex Optimization Approach AISTATS 2020 LMLFM: Longitudinal Multi-Level Factorization Machine AAAI 2020 Multi-task Additive Models for Robust Estimation and Automatic Structure Discovery NeurIPS 2020 On Efficient Adjustment in Causal Graphs JMLR 2020 Rank-based Lasso - efficient methods for high-dimensional robust model selection JMLR 2020 Sparse Learning with CART NeurIPS 2020 Stable Learning via Sample Reweighting AAAI 2020 The Complete Lasso Tradeoff Diagram NeurIPS 2020 Ultra-High Dimensional Single-Index Quantile Regression JMLR 2020 A Distillation Approach to Data Efficient Individual Treatment Effect Estimation AAAI 2019 ASAC: Active Sensing using Actor-Critic models MLHC 2019 Exact Combinatorial Optimization with Graph Convolutional Neural Networks NeurIPS 2019 Incorporating Grouping Information into Bayesian Decision Tree Ensembles ICML 2019