Chao Huang

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University of Notre Dame ∙ Shenzhen University

Representation Learning on Variable Length and Incomplete Wearable-Sensory Time Series

The prevalence of wearable sensors (e.g., smart wristband) is enabling a...
02/10/2020 ∙ by Xian Wu, et al. ∙ 8 ∙ share

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Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally ope...
06/01/2017 ∙ by Keith Feldman, et al. ∙ 0 ∙ share

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Transfer Adversarial Hashing for Hamming Space Retrieval

Hashing is widely applied to large-scale image retrieval due to the stor...
12/13/2017 ∙ by Zhangjie Cao, et al. ∙ 0 ∙ share

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Neural Tensor Factorization

Neural collaborative filtering (NCF) and recurrent recommender systems (...
02/13/2018 ∙ by Xian Wu, et al. ∙ 0 ∙ share

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Machine Friendly Machine Learning: Interpretation of Computed Tomography Without Image Reconstruction

Recent advancements in deep learning for automated image processing and ...
12/03/2018 ∙ by Hyunkwang Lee, et al. ∙ 0 ∙ share

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Extreme Image Compression via Multiscale Autoencoders With Generative Adversarial Optimization

We propose a MultiScale AutoEncoder(MSAE) based extreme image compressio...
04/08/2019 ∙ by Chao Huang, et al. ∙ 0 ∙ share

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Deep learning in bioinformatics: introduction, application, and perspective in big data era

Deep learning, which is especially formidable in handling big data, has ...
02/28/2019 ∙ by Yu Li, et al. ∙ 0 ∙ share

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Model predictive approach to integrated path planning and tracking for autonomous vehicles

In the path planning problem of autonomous application, the existing stu...
05/09/2019 ∙ by Chao Huang, et al. ∙ 0 ∙ share

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ReachNN: Reachability Analysis of Neural-Network Controlled Systems

Applying neural networks as controllers in dynamical systems has shown g...
06/25/2019 ∙ by Chao Huang, et al. ∙ 0 ∙ share

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Graph Fourier Transform Based on ℓ_1 Norm Variation Minimization

The definition of the graph Fourier transform is a fundamental issue in ...
08/19/2019 ∙ by Lihua Yang, et al. ∙ 0 ∙ share

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Heterogeneous Deep Graph Infomax

Graph representation learning is to learn universal node representations...
11/19/2019 ∙ by Yuxiang Ren, et al. ∙ 0 ∙ share

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Shape-Aware Organ Segmentation by Predicting Signed Distance Maps

In this work, we propose to resolve the issue existing in current deep l...
12/09/2019 ∙ by Yuan Xue, et al. ∙ 0 ∙ share

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Few-Shot Knowledge Graph Completion

Knowledge graphs (KGs) serve as useful resources for various natural lan...
11/26/2019 ∙ by Chuxu Zhang, et al. ∙ 0 ∙ share

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Inner Attention Supported Adaptive Cooperation for Heterogeneous Multi Robots Teaming based on Multi-agent Reinforcement Learning

Humans can selectively focus on different information based on different...
02/12/2020 ∙ by Chao Huang, et al. ∙ 0 ∙ share

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Chao Huang

Featured Co-authors

Jiawei Zhang

Bo Liu

Xin Chen

Yu Li

Wei Fan

Rui Liu

Shiliang Pu

Jianmin Wang

Xin Gao

Mingsheng Long

Tong Chen

Representation Learning on Variable Length and Incomplete Wearable-Sensory Time Series

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

Transfer Adversarial Hashing for Hamming Space Retrieval

Neural Tensor Factorization

Machine Friendly Machine Learning: Interpretation of Computed Tomography Without Image Reconstruction

Extreme Image Compression via Multiscale Autoencoders With Generative Adversarial Optimization

Deep learning in bioinformatics: introduction, application, and perspective in big data era

Model predictive approach to integrated path planning and tracking for autonomous vehicles

ReachNN: Reachability Analysis of Neural-Network Controlled Systems

Graph Fourier Transform Based on ℓ_1 Norm Variation Minimization

Heterogeneous Deep Graph Infomax

Shape-Aware Organ Segmentation by Predicting Signed Distance Maps

Few-Shot Knowledge Graph Completion

Inner Attention Supported Adaptive Cooperation for Heterogeneous Multi Robots Teaming based on Multi-agent Reinforcement Learning