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Feature Selection using Stochastic Gates

9 October 2018

Papers citing "Feature Selection using Stochastic Gates"

27 / 27 papers shown

Title
Sparse-Input Neural Network using Group Concave Regularization Bin Luo S. Halabi 163 3 0 01 Jul 2023
Feature Selection using Sparse Adaptive Bottleneck Centroid-Encoder T. Ghosh Michael Kirby 182 0 0 07 Jun 2023
$Enabling tabular deep learning when $d \gg n$ with an auxiliary knowledge graph$ Enabling tabular deep learning when $d \gg n$ with an auxiliary knowledge graph Camilo Ruiz Hongyu Ren Kexin Huang J. Leskovec 192 2 0 07 Jun 2023
One-step learning algorithm selection for classification via convolutional neural networksInformation Sciences (Inf. Sci.), 2023 S. Maldonado Carla Vairetti Ignacio Figueroa 159 0 0 16 May 2023
Improving the Robustness of Neural Multiplication Units with Reversible Stochasticity Bhumika Mistry K. Farrahi Jonathon S. Hare AAML 95 0 0 10 Nov 2022
DiSC: Differential Spectral Clustering of FeaturesNeural Information Processing Systems (NeurIPS), 2022 Ram Dyuthi Sristi Zhengchao Wan Ariel Jaffe 136 7 0 10 Nov 2022
SG-VAD: Stochastic Gates Based Speech Activity DetectionIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022 Jonathan Svirsky Ofir Lindenbaum 169 11 0 28 Oct 2022
Sequential Attention for Feature SelectionInternational Conference on Learning Representations (ICLR), 2022 T. Yasuda M. Bateni Lin Chen Matthew Fahrbach Gang Fu Vahab Mirrokni 316 11 0 29 Sep 2022
Learning to Increase the Power of Conditional Randomization TestsMachine-mediated learning (ML), 2022 Shalev Shaer Yaniv Romano CML 319 2 0 03 Jul 2022
Sparse Centroid-Encoder: A Nonlinear Model for Feature Selection T. Ghosh Michael Kirby 151 0 0 30 Jan 2022
Pruning-aware Sparse Regularization for Network PruningMachine Intelligence Research (MIR), 2022 Nanfei Jiang Xu Zhao Honghui Dong Yongqi An Ming Tang Jinqiao Wang 3DPC 154 16 0 18 Jan 2022
Training Deep Models to be Explained with Fewer Examples Tomoharu Iwata Yuya Yoshikawa FAtt 203 2 0 07 Dec 2021
Enhanced Exploration in Neural Feature Selection for Deep Click-Through Rate Prediction Models via Ensemble of Gating Layers L. Guan Xia Xiao Ming-yue Chen Youlong Cheng 140 2 0 07 Dec 2021
A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift GeneralizationInternational Conference on Machine Learning (ICML), 2021 Renzhe Xu Xingxuan Zhang Zheyan Shen Tong Zhang Peng Cui OOD 344 31 0 03 Nov 2021
Support Recovery with Stochastic Gates: Theory and Application for Linear ModelsSignal Processing (Signal Process.), 2021 Soham Jana Henry Li Yutaro Yamada Ofir Lindenbaum 313 7 0 29 Oct 2021
Few-shot Learning for Unsupervised Feature Selection Atsutoshi Kumagai Tomoharu Iwata Yasuhiro Fujiwara SSL 159 6 0 02 Jul 2021
Top- $k$ Regularization for Supervised Feature Selection Xinxing Wu Q. Cheng 136 1 0 04 Jun 2021
RAIDER: Reinforcement-aided Spear Phishing DetectorInternational Conference on Network and System Security (ICNSS), 2021 Keelan Evans A. Abuadbba Tingmin Wu Kristen Moore Mohiuddin Ahmed Ganna Pogrebna Surya Nepal Mike Johnstone AAML 260 14 0 17 May 2021
Refined Least Squares for Support RecoverySignal Processing (Signal Process.), 2021 Ofir Lindenbaum Stefan Steinerberger 95 6 0 19 Mar 2021
$$\ell_0$-based Sparse Canonical Correlation Analysis$ $\ell_0$ -based Sparse Canonical Correlation Analysis Ofir Lindenbaum Moshe Salhov Amir Averbuch Y. Kluger 228 1 0 12 Oct 2020
Differentiable Unsupervised Feature Selection based on a Gated Laplacian Ofir Lindenbaum Uri Shaham Jonathan Svirsky Erez Peterfreund Y. Kluger 309 6 0 09 Jul 2020
Learning to Ask Medical Questions using Reinforcement LearningMachine Learning in Health Care (MLHC), 2020 Uri Shaham Tom Zahavy C. Caraballo S. Mahajan D. Massey H. Krumholz OOD 190 2 0 31 Mar 2020
Randomly Aggregated Least Squares for Support RecoverySignal Processing (Signal Process.), 2020 Ofir Lindenbaum Stefan Steinerberger FedML 171 11 0 16 Mar 2020
FsNet: Feature Selection Network on High-dimensional Biological DataIEEE International Joint Conference on Neural Network (IJCNN), 2020 Dinesh Singh Héctor Climente-González Mathis Petrovich Eiryo Kawakami M. Yamada 305 54 0 23 Jan 2020
Learning Deep Attribution Priors Based On Prior Knowledge Ethan Weinberger Joseph D. Janizek Su-In Lee FAtt 121 1 0 20 Dec 2019
Sobolev Independence CriterionNeural Information Processing Systems (NeurIPS), 2019 Youssef Mroueh Tom Sercu Mattia Rigotti Inkit Padhi Cicero Nogueira dos Santos 170 5 0 31 Oct 2019
Not All Features Are Equal: Feature Leveling Deep Neural Networks for Better Interpretation Yingjing Lu Runde Yang MILM 128 2 0 24 May 2019