4 papers
Boosting Co-teaching with Compression Regularization for Label Noise
Yingyi Chen, Xi Shen, Shell Xu Hu +1
In this paper, we study the problem of learning image classification models in the presence of label noise. We revisit a simple compression regularization named Nested Dropout. We…
Unified Framework for Feature Extraction based on Contrastive Learning
Hongjie Zhang
Feature extraction is an efficient approach for alleviating the issue of dimensionality in high-dimensional data. As a popular self-supervised learning method, contrastive learning…
Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures
Fanghui Liu, Xiaolin Huang, Yingyi Chen +1
In this paper, we attempt to solve a long-lasting open question for non-positive definite (non-PD) kernels in machine learning community: can a given non-PD kernel be decomposed in…
Two-stage Best-scored Random Forest for Large-scale Regression
Hanyuan Hang, Yingyi Chen, Johan A. K. Suykens
We propose a novel method designed for large-scale regression problems, namely the two-stage best-scored random forest (TBRF). "Best-scored" means to select one regression tree wit…