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236 results on '"Tu, Yiheng"'

6. A Simple Approach to Automated Spectral Clustering

Author

Fan, Jicong, Tu, Yiheng, Zhang, Zhao, Zhao, Mingbo, and Zhang, Haijun

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

The performance of spectral clustering heavily relies on the quality of affinity matrix. A variety of affinity-matrix-construction (AMC) methods have been proposed but they have hyperparameters to determine beforehand, which requires strong experience and leads to difficulty in real applications, especially when the inter-cluster similarity is high and/or the dataset is large. In addition, we often need to choose different AMC methods for different datasets, which still depends on experience. To solve these two challenging problems, in this paper, we present a simple yet effective method for automated spectral clustering. First, we propose to find the most reliable affinity matrix via grid search or Bayesian optimization among a set of candidates given by different AMC methods with different hyperparameters, where the reliability is quantified by the \textit{relative-eigen-gap} of graph Laplacian introduced in this paper. Second, we propose a fast and accurate AMC method based on least squares representation and thresholding and prove its effectiveness theoretically. Finally, we provide a large-scale extension for the automated spectral clustering method, of which the time complexity is linear with the number of data points. Extensive experiments of natural image clustering show that our method is more versatile, accurate, and efficient than baseline methods., Comment: Accepted by NeurIPS 2022

Published
2021

20. Applying Eye Tracking to Identify Autism Spectrum Disorder in Children

Author

Wan, Guobin, Kong, Xuejun, Sun, Binbin, Yu, Siyi, Tu, Yiheng, Park, Joel, Lang, Courtney, Koh, Madelyn, Wei, Zhen, Feng, Zhe, Lin, Yan, and Kong, Jian

Abstract

Eye tracking (ET) holds potential for the early detection of autism spectrum disorder (ASD). To overcome the difficulties of working with young children, developing a short and informative paradigm is crucial for ET. We investigated the fixation times of 37 ASD and 37 typically developing (TD) children ages 4-6 watching a 10-second video of a female speaking. ASD children showed significant reductions in fixation time at six areas of interest. Furthermore, discriminant analysis revealed fixation times at the mouth and body could significantly discriminate ASD from TD with a classification accuracy of 85.1%, sensitivity of 86.5%, and specificity of 83.8%. Our study suggests that a short video clip may provide enough information to distinguish ASD from TD children.

Published
2019
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40. Functional and structural brain reorganization in patients with ischemic stroke: a multimodality MRI fusion study

Author

Cui, Fangyuan, primary, Zhao, Lei, additional, Lu, Mengxin, additional, Liu, Ruoyi, additional, Lv, Qiuyi, additional, Lin, Dan, additional, Li, Kuangshi, additional, Zhang, Yong, additional, Wang, Yahui, additional, Wang, Yue, additional, Wang, Liping, additional, Tan, Zhongjian, additional, Tu, Yiheng, additional, and Zou, Yihuai, additional

Published
2023
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