2 code implementations • ACM Transactions on Multimedia Computing, Communications, and Applications 2024 • Mingyu Li, Tao Zhou, Zhuo Huang, Jian Yang, Jie Yang, Chen Gong
Nowadays, class-mismatch problem has drawn intensive attention in Semi-Supervised Learning (SSL), where the classes of labeled data are assumed to be only a subset of the classes of unlabeled data.
2 code implementations • 5 Dec 2023 • Zhuo Huang, Chang Liu, Yinpeng Dong, Hang Su, Shibao Zheng, Tongliang Liu
Concretely, by estimating a transition matrix that captures the probability of one class being confused with another, an instruction containing a correct exemplar and an erroneous one from the most probable noisy class can be constructed.
no code implementations • 25 Oct 2023 • Zhuo Huang, Muyang Li, Li Shen, Jun Yu, Chen Gong, Bo Han, Tongliang Liu
By fully exploring both variant and invariant parameters, our EVIL can effectively identify a robust subnetwork to improve OOD generalization.
1 code implementation • NeurIPS 2023 • Zhuo Huang, Li Shen, Jun Yu, Bo Han, Tongliang Liu
Therefore, the label guidance on labeled data is hard to be propagated to unlabeled data.
3 code implementations • CVPR 2023 • Zhuo Huang, Miaoxi Zhu, Xiaobo Xia, Li Shen, Jun Yu, Chen Gong, Bo Han, Bo Du, Tongliang Liu
Experimentally, we simulate photon-limited corruptions using CIFAR10/100 and ImageNet30 datasets and show that SharpDRO exhibits a strong generalization ability against severe corruptions and exceeds well-known baseline methods with large performance gains.
1 code implementation • 7 Jul 2022 • Zhuo Huang, Xiaobo Xia, Li Shen, Bo Han, Mingming Gong, Chen Gong, Tongliang Liu
Machine learning models are vulnerable to Out-Of-Distribution (OOD) examples, and such a problem has drawn much attention.
no code implementations • 10 Dec 2021 • Chen Tong, Peter Reinhard Hansen, Zhuo Huang
We introduce a new volatility model for option pricing that combines Markov switching with the Realized GARCH framework.
no code implementations • 10 Dec 2021 • Peter Reinhard Hansen, Zhuo Huang, Chen Tong, Tianyi Wang
The volatility shock endows the exponentially affine SDF with a compensation for volatility risk.
no code implementations • NeurIPS 2021 • Zhuo Huang, Chao Xue, Bo Han, Jian Yang, Chen Gong
Universal Semi-Supervised Learning (UniSSL) aims to solve the open-set problem where both the class distribution (i. e., class set) and feature distribution (i. e., feature domain) are different between labeled dataset and unlabeled dataset.
no code implementations • 27 Nov 2020 • Zhuo Huang, Ying Tai, Chengjie Wang, Jian Yang, Chen Gong
Semi-Supervised Learning (SSL) with mismatched classes deals with the problem that the classes-of-interests in the limited labeled data is only a subset of the classes in massive unlabeled data.
no code implementations • 29 Nov 2019 • Weikaixin Kong, Xinyu Tu, Zhengwei Xie, Zhuo Huang
We used machine learning methods to predict NaV1. 7 inhibitors and found the model RF-CDK that performed best on the imbalanced dataset.