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Feature Selection

462 directly classified papers

Papers per year

Papers

More Efficient Estimation of Multivariate Additive Models Based on Tensor Decomposition and Penalization JMLR 2024
Embedded Feature Selection on Graph-Based Multi-View Clustering AAAI 2024
End-to-end Feature Selection Approach for Learning Skinny Trees AISTATS 2024
Variable Importance in High-Dimensional Settings Requires Grouping AAAI 2024
Supervised Feature Selection via Ensemble Gradient Information from Sparse Neural Networks AISTATS 2024
Generator Assisted Mixture of Experts for Feature Acquisition in Batch AAAI 2024
Feature Distribution Matching by Optimal Transport for Effective and Robust Coreset Selection AAAI 2024
Contributing Dimension Structure of Deep Feature for Coreset Selection AAAI 2024
On Sparse Canonical Correlation Analysis NIPS 2024
Text vs. Transcription: A Study of Differences Between the Writing and Speeches of U.S. Presidents EMNLP 2024
Not All Diffusion Model Activations Have Been Evaluated as Discriminative Features NIPS 2024
Decorrelated Variable Importance JMLR 2024
L0Learn: A Scalable Package for Sparse Learning using L0 Regularization JMLR 2023
Sparse Markov Models for High-dimensional Inference JMLR 2023
DRCFS: Doubly Robust Causal Feature Selection ICML 2023
Anti-drifting Feature Selection via Deep Reinforcement Learning (Student Abstract) AAAI 2023
Enhancing Argument Structure Extraction with Efficient Leverage of Contextual Information EMNLP 2023
Finding Support Examples for In-Context Learning EMNLP 2023
Dimension Reduction in Contextual Online Learning via Nonparametric Variable Selection JMLR 2023
Group SLOPE Penalized Low-Rank Tensor Regression JMLR 2023
Tilted Sparse Additive Models ICML 2023
Kernel Sufficient Dimension Reduction and Variable Selection for Compositional Data via Amalgamation ICML 2023
PED-ANOVA: Efficiently Quantifying Hyperparameter Importance in Arbitrary Subspaces IJCAI 2023
Identifying Context-Dependent Translations for Evaluation Set Production EMNLP 2023
A Randomized Subspace-based Approach for Dimensionality Reduction and Important Variable Selection JMLR 2023