Wei Huang

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University of Technology Sydney ∙ Zhejiang University ∙ NetEase, Inc

Wide Graph Neural Networks: Aggregation Provably Leads to Exponentially Trainability Loss

Graph convolutional networks (GCNs) and their variants have achieved gre...
03/03/2021 ∙ by Wei Huang, et al. ∙ 0 ∙ share

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Fairness and Accuracy in Federated Learning

In the federated learning setting, multiple clients jointly train a mode...
12/18/2020 ∙ by Wei Huang, et al. ∙ 4 ∙ share

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Implicit bias of deep linear networks in the large learning rate phase

Correctly choosing a learning rate (scheme) for gradient-based optimizat...
11/25/2020 ∙ by Wei Huang, et al. ∙ 8 ∙ share

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Formal Verification of Robustness and Resilience of Learning-Enabled State Estimation Systems for Robotics

This paper presents a formal verification guided approach for a principl...
10/16/2020 ∙ by Wei Huang, et al. ∙ 0 ∙ share

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Embedding and Synthesis of Knowledge in Tree Ensemble Classifiers

This paper studies the embedding and synthesis of knowledge in tree ense...
10/16/2020 ∙ by Wei Huang, et al. ∙ 24 ∙ share

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Rethinking Image Inpainting via a Mutual Encoder-Decoder with Feature Equalizations

Deep encoder-decoder based CNNs have advanced image inpainting methods f...
07/14/2020 ∙ by Hongyu Liu, et al. ∙ 0 ∙ share

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Achievable Rate Region of MISO Interference Channel Aided by Intelligent Reflecting Surface

This paper investigates the achievable rate region of the multiple-input...
05/19/2020 ∙ by Wei Huang, et al. ∙ 0 ∙ share

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On the Neural Tangent Kernel of Deep Networks with Orthogonal Initialization

In recent years, a critical initialization scheme with orthogonal initia...
04/13/2020 ∙ by Wei Huang, et al. ∙ 14 ∙ share

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Gaussian Process Latent Variable Model Factorization for Context-aware Recommender Systems

Context-aware recommender systems (CARS) have gained increasing attentio...
12/19/2019 ∙ by Wei Huang, et al. ∙ 11 ∙ share

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Mean field theory for deep dropout networks: digging up gradient backpropagation deeply

In recent years, the mean field theory has been applied to the study of ...
12/19/2019 ∙ by Wei Huang, et al. ∙ 23 ∙ share

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One-Stage Inpainting with Bilateral Attention and Pyramid Filling Block

Recent deep learning based image inpainting methods which utilize contex...
12/18/2019 ∙ by Hongyu Liu, et al. ∙ 17 ∙ share

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Test Metrics for Recurrent Neural Networks

Recurrent neural networks (RNNs) have been applied to a broad range of a...
11/05/2019 ∙ by Wei Huang, et al. ∙ 15 ∙ share

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SoK: Hardware Security Support for Trustworthy Execution

In recent years, there have emerged many new hardware mechanisms for imp...
10/11/2019 ∙ by Lianying Zhao, et al. ∙ 0 ∙ share

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testRNN: Coverage-guided Testing on Recurrent Neural Networks

Recurrent neural networks (RNNs) have been widely applied to various seq...
06/20/2019 ∙ by Wei Huang, et al. ∙ 2 ∙ share

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Attributes-aided Part Detection and Refinement for Person Re-identification

Person attributes are often exploited as mid-level human semantic inform...
02/27/2019 ∙ by Shuzhao Li, et al. ∙ 0 ∙ share

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Implications of Integrated CPU-GPU Processors on Thermal and Power Management Techniques

Heterogeneous processors with architecturally different cores (CPU and G...
08/29/2018 ∙ by Kapil Dev, et al. ∙ 0 ∙ share

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Multiobjective Optimization Differential Evolution Enhanced with Principle Component Analysis for Constrained Optimization

Multiobjective optimization evolutionary algorithms have been successful...
05/01/2018 ∙ by Wei Huang, et al. ∙ 0 ∙ share

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QoE-Oriented Resource Allocation for 360-degree Video Transmission over Heterogeneous Networks

Immersive media streaming, especially virtual reality (VR)/360-degree vi...
03/21/2018 ∙ by Wei Huang, et al. ∙ 0 ∙ share

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Wei Huang

Featured Co-authors

Jing Zhang

Chao Yang

Jun He

Yong Zeng

Xiaowei Huang

Tianrui Li

Tao Xu

Junbo Zhang

Richard Yi Da Xu

Jenq-Neng Hwang

Yongming Huang

Wide Graph Neural Networks: Aggregation Provably Leads to Exponentially Trainability Loss

Fairness and Accuracy in Federated Learning

Implicit bias of deep linear networks in the large learning rate phase

Formal Verification of Robustness and Resilience of Learning-Enabled State Estimation Systems for Robotics

Embedding and Synthesis of Knowledge in Tree Ensemble Classifiers

Rethinking Image Inpainting via a Mutual Encoder-Decoder with Feature Equalizations

Achievable Rate Region of MISO Interference Channel Aided by Intelligent Reflecting Surface

On the Neural Tangent Kernel of Deep Networks with Orthogonal Initialization

Gaussian Process Latent Variable Model Factorization for Context-aware Recommender Systems

Mean field theory for deep dropout networks: digging up gradient backpropagation deeply

One-Stage Inpainting with Bilateral Attention and Pyramid Filling Block

Test Metrics for Recurrent Neural Networks

SoK: Hardware Security Support for Trustworthy Execution

testRNN: Coverage-guided Testing on Recurrent Neural Networks

Attributes-aided Part Detection and Refinement for Person Re-identification

Implications of Integrated CPU-GPU Processors on Thermal and Power Management Techniques

Multiobjective Optimization Differential Evolution Enhanced with Principle Component Analysis for Constrained Optimization

QoE-Oriented Resource Allocation for 360-degree Video Transmission over Heterogeneous Networks