no code implementations • 3 Dec 2024 • Pengjie Zhou, Haoyu Wei, Huiming Zhang
Reinforcement Learning (RL) is a widely researched area in artificial intelligence that focuses on teaching agents decision-making through interactions with their environment.
no code implementations • 13 Mar 2023 • Huiming Zhang, Haoyu Wei, Guang Cheng
In non-asymptotic learning, variance-type parameters of sub-Gaussian distributions are of paramount importance.
no code implementations • ICCV 2023 • Jiong Wang, Huiming Zhang, Haiwen Hong, Xuan Jin, Yuan He, Hui Xue, Zhou Zhao
For the classification task, we introduce an open corpus classifier by reconstructing original classifier with similar words in text space.
no code implementations • 28 Dec 2022 • Fang Xie, Lihu Xu, Qiuran Yao, Huiming Zhang
This paper studies the distribution estimation of contaminated data by the MoM-GAN method, which combines generative adversarial net (GAN) and median-of-mean (MoM) estimation.
no code implementations • 11 Feb 2022 • Haoyu Wei, Xiaoyu Lei, Yixin Han, Huiming Zhang
Identifying important features linked to a response variable is a fundamental task in various scientific domains.
no code implementations • 10 Jan 2022 • Lihu Xu, Fang Yao, Qiuran Yao, Huiming Zhang
There has been a surge of interest in developing robust estimators for models with heavy-tailed and bounded variance data in statistics and machine learning, while few works impose unbounded variance.
1 code implementation • NeurIPS 2021 • Haibo Chen, Lei Zhao, Zhizhong Wang, Huiming Zhang, Zhiwen Zuo, Ailin Li, Wei Xing, Dongming Lu
Although existing artistic style transfer methods have achieved significant improvement with deep neural networks, they still suffer from artifacts such as disharmonious colors and repetitive patterns.
1 code implementation • 22 Oct 2021 • Yang Zhang, Moyun Liu, Huiming Zhang, Guodong Sun, Jingwu He
To reduce time complexity while improving performance, a sparse representation of global nodes based on noise-free online low-rank representation is used to obtain a global graph at each scale.
no code implementations • CVPR 2021 • Haibo Chen, Lei Zhao, Zhizhong Wang, Huiming Zhang, Zhiwen Zuo, Ailin Li, Wei Xing, Dongming Lu
Artistic style transfer is an image editing task that aims at repainting everyday photographs with learned artistic styles.
no code implementations • 2 May 2021 • Chang Cui, Jinzhu Jia, Yijun Xiao, Huiming Zhang
Using the debiased estimator, we establish multiple testing procedures.
no code implementations • 4 Feb 2021 • Huiming Zhang, Haoyu Wei
Constant-specified and exponential concentration inequalities play an essential role in the finite-sample theory of machine learning and high-dimensional statistics area.
no code implementations • 31 Jan 2021 • Yang Zhang, Moyun Liu, Yang Yang, Yanwen Guo, Huiming Zhang
Real-time fault detection for freight trains plays a vital role in guaranteeing the security and optimal operation of railway transportation under stringent resource requirements.
no code implementations • ICCV 2021 • Haibo Chen, Lei Zhao, Huiming Zhang, Zhizhong Wang, Zhiwen Zuo, Ailin Li, Wei Xing, Dongming Lu
Image style transfer aims to transfer the styles of artworks onto arbitrary photographs to create novel artistic images.
no code implementations • 4 Nov 2020 • Huiming Zhang, Song Xi Chen
This paper gives a review of concentration inequalities which are widely employed in non-asymptotical analyses of mathematical statistics in a wide range of settings, from distribution-free to distribution-dependent, from sub-Gaussian to sub-exponential, sub-Gamma, and sub-Weibull random variables, and from the mean to the maximum concentration.
no code implementations • 10 Sep 2020 • Huiming Zhang, Xiaoyu Lei
From the non-asymptotic point of view, we focus on the rate-optimal upper and lower bounds of the prediction error.
no code implementations • 11 Jun 2020 • Huamei Huang, Yujing Gao, Huiming Zhang, Bo Li
When we are interested in high-dimensional system and focus on classification performance, the $\ell_{1}$-penalized logistic regression is becoming important and popular.
no code implementations • 21 May 2020 • Jun Yu, HaiYing Wang, Mingyao Ai, Huiming Zhang
We first derive optimal Poisson subsampling probabilities in the context of quasi-likelihood estimation under the A- and L-optimality criteria.
no code implementations • ICLR 2020 • Zhiwen Zuo, Lei Zhao, Huiming Zhang, Qihang Mo, Haibo Chen, Zhizhong Wang, Ailin Li, Lihong Qiu, Wei Xing, Dongming Lu
Generative Adversarial Networks (GANs) have shown impressive results in modeling distributions over complicated manifolds such as those of natural images.
no code implementations • 14 Nov 2019 • Xiaowei Yang, Huiming Zhang, Haoyu Wei, Shouzheng Zhang
It shows that our method has potency and superiority of detecting the shape of multi-mode density compared with other conventional approaches.
no code implementations • 9 Dec 2017 • Huiming Zhang, Jinzhu Jia
We study a sparse negative binomial regression (NBR) for count data by showing the non-asymptotic advantages of using the elastic-net estimator.