TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization

9 March 2023

Papers citing "TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization"

7 / 7 papers shown

Title
TabSeq: A Framework for Deep Learning on Tabular Data via Sequential Ordering A. Habib Kesheng Wang Mary-Anne Hartley Gianfranco Doretto Donald Adjeroh LMTD 21 1 0 17 Oct 2024
Canonical normalizing flows for manifold learning Kyriakos Flouris E. Konukoglu DRL 38 7 0 19 Oct 2023
Joint Training of Deep Ensembles Fails Due to Learner Collusion Alan Jeffares Tennison Liu Jonathan Crabbé M. Schaar FedML 23 15 0 26 Jan 2023
Transfer Learning with Deep Tabular Models Roman Levin Valeriia Cherepanova Avi Schwarzschild Arpit Bansal C. B. Bruss Tom Goldstein A. Wilson Micah Goldblum OOD FedML LMTD 66 58 0 30 Jun 2022
A Survey on Neural Network Interpretability Yu Zhang Peter Tiño A. Leonardis K. Tang FaML XAI 129 654 0 28 Dec 2020
Frankenstein: Learning Deep Face Representations using Small Data Guosheng Hu Xiaojiang Peng Yongxin Yang Timothy M. Hospedales Jakob Verbeek CVBM 58 121 0 21 Mar 2016
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 243 7,597 0 03 Jul 2012