3 citations · 8 across the 10 of their papers we have counts for
Showing 2023Show all
3 papers · 1 filter
cs.LG2023★ 3 cited
Robust-GBDT: GBDT with Nonconvex Loss for Tabular Classification in the Presence of Label Noise and Class Imbalance
Jiaqi Luo, Yuedong Quan, Shixin Xu
Dealing with label noise in tabular classification tasks poses a persistent challenge in machine learning. While robust boosting methods have shown promise in binary classification…
cs.LG2023★ 1 cited
NCART: Neural Classification and Regression Tree for Tabular Data
Jiaqi Luo, Shixin Xu
Deep learning models have become popular in the analysis of tabular data, as they address the limitations of decision trees and enable valuable applications like semi-supervised le…
cs.LG2023
Generating Adversarial Examples with Better Transferability via Masking Unimportant Parameters of Surrogate Model
Dingcheng Yang, Wenjian Yu, Zihao Xiao +1
Deep neural networks (DNNs) have been shown to be vulnerable to adversarial examples. Moreover, the transferability of the adversarial examples has received broad attention in rece…