variable selection

Integral-based Knockoffs Inference for Partially Linear Models AAAI 2026 Planning in Branch-and-Bound: Model-Based Reinforcement Learning for Exact Combinatorial Optimization AAAI 2026 Separating Oblivious and Adaptive Models of Variable Selection (Extended Abstract) COLT 2026 Sparse recovery of Diffusion Dynamics: Handling High-Dimensionality in Repeated Short Trajectories UAI 2026 Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large p ICML 2025 A Differentiable Rank-Based Objective for Better Feature Learning ICLR 2025 Asymptotic Inference for Multi-Stage Stationary Treatment Policy with Variable Selection JMLR 2025 High Dimensional Bayesian Optimization using Lasso Variable Selection AISTATS 2025 Knockoffs Inference for Partially Linear Models with Automatic Structure Discovery AAAI 2025 PCM Selector: Penalized Covariate-Mediator Selection Operator for Evaluating Linear Causal Effects AAAI 2025 Spike-and-Slab Posterior Sampling in High Dimensions COLT 2025 Transformer Learns Optimal Variable Selection in Group-Sparse Classification ICLR 2025 CAMBranch: Contrastive Learning with Augmented MILPs for Branching ICLR 2024 ENNS: Variable Selection, Regression, Classification, and Deep Neural Network for High-Dimensional Data JMLR 2024 Estimating Conditional Average Treatment Effects via Sufficient Representation Learning IJCAI 2024 Heterogeneity-aware Clustered Distributed Learning for Multi-source Data Analysis JMLR 2024 More Efficient Estimation of Multivariate Additive Models Based on Tensor Decomposition and Penalization JMLR 2024 On Sufficient Graphical Models JMLR 2024 Sample Quality Heterogeneity-aware Federated Causal Discovery through Adaptive Variable Space Selection IJCAI 2024 Statistical analysis for a penalized EM algorithm in high-dimensional mixture linear regression model JMLR 2024 Transfer learning for tensor Gaussian graphical models JMLR 2024 Unified Transfer Learning in High-Dimensional Linear Regression AISTATS 2024 A Randomized Subspace-based Approach for Dimensionality Reduction and Important Variable Selection JMLR 2023 Bayesian Variable Selection in a Million Dimensions AISTATS 2023 Computationally Efficient High-Dimensional Bayesian Optimization via Variable Selection AutoML 2023