Sparse-Input Neural Networks for High-dimensional Nonparametric Regression and Classification

21 November 2017

Papers citing "Sparse-Input Neural Networks for High-dimensional Nonparametric Regression and Classification"

17 / 17 papers shown

Title
Representation Retrieval Learning for Heterogeneous Data Integration Qi Xu Annie Qu 57 0 0 12 Mar 2025
Regularization can make diffusion models more efficient Mahsa Taheri Johannes Lederer 102 0 0 13 Feb 2025
End-to-end Feature Selection Approach for Learning Skinny Trees Shibal Ibrahim Kayhan Behdin Rahul Mazumder 30 0 0 28 Oct 2023
The Contextual Lasso: Sparse Linear Models via Deep Neural Networks Ryan Thompson Amir Dezfouli Robert Kohn 33 4 0 02 Feb 2023
Statistical guarantees for sparse deep learning Johannes Lederer 21 11 0 11 Dec 2022
Weight Predictor Network with Feature Selection for Small Sample Tabular Biomedical Data Andrei Margeloiu Nikola Simidjievski Pietro Lio M. Jamnik 32 12 0 28 Nov 2022
DisPositioNet: Disentangled Pose and Identity in Semantic Image Manipulation Azade Farshad Yousef Yeganeh Helisa Dhamo F. Tombari Nassir Navab DiffM OCL DRL CoGe 29 4 0 10 Nov 2022
Statistical Guarantees for Approximate Stationary Points of Simple Neural Networks Mahsa Taheri Fang Xie Johannes Lederer 31 0 0 09 May 2022
Lockout: Sparse Regularization of Neural Networks Gilmer Valdes W. Arbelo Y. Interian J. Friedman 19 2 0 15 Jul 2021
Consistent Sparse Deep Learning: Theory and Computation Y. Sun Qifan Song F. Liang BDL 45 27 0 25 Feb 2021
Interpretability and Explainability: A Machine Learning Zoo Mini-tour Ricards Marcinkevics Julia E. Vogt XAI 28 119 0 03 Dec 2020
Layer Sparsity in Neural Networks Mohamed Hebiri Johannes Lederer 36 10 0 28 Jun 2020
Ensembled sparse-input hierarchical networks for high-dimensional datasets Jean Feng N. Simon 19 4 0 11 May 2020
LassoNet: A Neural Network with Feature Sparsity Ismael Lemhadri Feng Ruan L. Abraham Robert Tibshirani 26 122 0 29 Jul 2019
Improving performance of deep learning models with axiomatic attribution priors and expected gradients G. Erion Joseph D. Janizek Pascal Sturmfels Scott M. Lundberg Su-In Lee OOD BDL FAtt 21 80 0 25 Jun 2019
Neural Granger Causality Alex Tank Ian Covert N. Foti Ali Shojaie E. Fox CML 25 100 0 16 Feb 2018
High-dimensional additive modeling L. Meier Sara van de Geer Peter Buhlmann 201 481 0 25 Jun 2008