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Picture for Ling Huang

Evidential segmentation of 3D PET/CT images


Apr 27, 2021
Ling Huang, Su Ruan, Pierre Decazes, Thierry Denoeux

* Belief2021 

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BCFNet: A Balanced Collaborative Filtering Network with Attention Mechanism


Mar 10, 2021
Chang-Dong Wang, Zi-Yuan Hu, Jin Huang, Zhi-Hong Deng, Ling Huang, Jian-Huang Lai, Philip S. Yu


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Belief function-based semi-supervised learning for brain tumor segmentation


Jan 29, 2021
Ling Huang, Su Ruan, Thierry Denoeux

* 5 pages, 4 figures, ISBI2021 conference 

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Covid-19 classification with deep neural network and belief functions


Jan 18, 2021
Ling Huang, Su Ruan, Thierry Denoeux

* medical image, Covid-19, belief function, BIHI conference 

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Modeling Heterogeneous Statistical Patterns in High-dimensional Data by Adversarial Distributions: An Unsupervised Generative Framework


Dec 15, 2020
Han Zhang, Wenhao Zheng, Charley Chen, Kevin Gao, Yao Hu, Ling Huang, Wei Xu


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DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System


Jan 15, 2019
Zhi-Hong Deng, Ling Huang, Chang-Dong Wang, Jian-Huang Lai, Philip S. Yu


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DIAG-NRE: A Deep Pattern Diagnosis Framework for Distant Supervision Neural Relation Extraction


Nov 06, 2018
Shun Zheng, Peilin Yu, Lu Chen, Ling Huang, Wei Xu


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Online Semi-Supervised Learning on Quantized Graphs


Mar 15, 2012
Michal Valko, Branislav Kveton, Ling Huang, Daniel Ting

* Appears in Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (UAI2010) 

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An Analysis of the Convergence of Graph Laplacians


Jan 28, 2011
Daniel Ting, Ling Huang, Michael Jordan


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Mantis: Predicting System Performance through Program Analysis and Modeling


Sep 30, 2010
Byung-Gon Chun, Ling Huang, Sangmin Lee, Petros Maniatis, Mayur Naik


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Query Strategies for Evading Convex-Inducing Classifiers


Jul 03, 2010
Blaine Nelson, Benjamin I. P. Rubinstein, Ling Huang, Anthony D. Joseph, Steven J. Lee, Satish Rao, J. D. Tygar


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Near-Optimal Evasion of Convex-Inducing Classifiers


Mar 14, 2010
Blaine Nelson, Benjamin I. P. Rubinstein, Ling Huang, Anthony D. Joseph, Shing-hon Lau, Steven J. Lee, Satish Rao, Anthony Tran, J. D. Tygar

* 8 pages; to appear at AISTATS'2010 

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Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning


Nov 30, 2009
Benjamin I. P. Rubinstein, Peter L. Bartlett, Ling Huang, Nina Taft

* 21 pages, 1 figure 

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