On Universal Features for High-Dimensional Learning and Inference

20 November 2019

Papers citing "On Universal Features for High-Dimensional Learning and Inference"

7 / 7 papers shown

Title
Separable Computation of Information Measures Xiangxiang Xu Lizhong Zheng 31 0 0 28 Jan 2025
Kernel Subspace and Feature Extraction Xiangxiang Xu Lizhong Zheng 23 0 0 04 Jan 2023
An Information-Theoretic Approach to Transferability in Task Transfer Learning Yajie Bao Yongni Li Shao-Lun Huang Lin Zhang Lizhong Zheng Amir Zamir Leonidas J. Guibas 17 117 0 20 Dec 2022
PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks Nan Ding Xi Chen Tomer Levinboim Soravit Changpinyo Radu Soricut 22 26 0 10 Mar 2022
Gradient-Based Empirical Risk Minimization using Local Polynomial Regression Ali Jadbabaie A. Makur Devavrat Shah 28 6 0 04 Nov 2020
An Information Theoretic Interpretation to Deep Neural Networks Shao-Lun Huang Xiangxiang Xu Lizhong Zheng G. Wornell FAtt 22 41 0 16 May 2019
Convex Sparse Matrix Factorizations Francis R. Bach Julien Mairal Jean Ponce 137 143 0 10 Dec 2008