b'Wei Huang'

research

∙ 05/17/2022

Hierarchical Distribution-Aware Testing of Deep Learning

With its growing use in safety/security-critical applications, Deep Lear...

Wei Huang, et al. ∙

research

∙ 05/11/2022

Deep Architecture Connectivity Matters for Its Convergence: A Fine-Grained Analysis

Advanced deep neural networks (DNNs), designed by either human or AutoML...

Wuyang Chen, et al. ∙

research

∙ 05/07/2022

Playing Tic-Tac-Toe Games with Intelligent Single-pixel Imaging

Single-pixel imaging (SPI) is a novel optical imaging technique by repla...

Shuming Jiao, et al. ∙

research

∙ 04/11/2022

Augmentation-Free Graph Contrastive Learning

Graph contrastive learning (GCL) is the most representative and prevalen...

Haonan Wang, et al. ∙

research

∙ 03/11/2022

Enhancing Adversarial Training with Second-Order Statistics of Weights

Adversarial training has been shown to be one of the most effective appr...

Gaojie Jin, et al. ∙

research

∙ 03/10/2022

An Audio-Visual Attention Based Multimodal Network for Fake Talking Face Videos Detection

DeepFake based digital facial forgery is threatening the public media se...

Ganglai Wang, et al. ∙

research

∙ 03/08/2022

Attention-Based Lip Audio-Visual Synthesis for Talking Face Generation in the Wild

Talking face generation with great practical significance has attracted ...

Ganglai Wang, et al. ∙

research

∙ 03/05/2022

Audio-visual speech separation based on joint feature representation with cross-modal attention

Multi-modal based speech separation has exhibited a specific advantage o...

Junwen Xiong, et al. ∙

research

∙ 03/04/2022

Look&Listen: Multi-Modal Correlation Learning for Active Speaker Detection and Speech Enhancement

Active speaker detection and speech enhancement have become two increasi...

Junwen Xiong, et al. ∙

research

∙ 02/24/2022

Auto-scaling Vision Transformers without Training

This work targets automated designing and scaling of Vision Transformers...

Wuyang Chen, et al. ∙

research

∙ 02/04/2022

Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning

PAC-Bayesian is an analysis framework where the training error can be ex...

Wei Huang, et al. ∙

research

∙ 01/29/2022

Achieving Efficient Distributed Machine Learning Using a Novel Non-Linear Class of Aggregation Functions

Distributed machine learning (DML) over time-varying networks can be an ...

Haizhou Du, et al. ∙

research

∙ 12/30/2021

THE Benchmark: Transferable Representation Learning for Monocular Height Estimation

Generating 3D city models rapidly is crucial for many applications. Mono...

Zhitong Xiong, et al. ∙

research

∙ 11/30/2021

Reliability Assessment and Safety Arguments for Machine Learning Components in Assuring Learning-Enabled Autonomous Systems

The increasing use of Machine Learning (ML) components embedded in auton...

Xingyu Zhao, et al. ∙

research

∙ 11/25/2021

Semantic-Aware Generation for Self-Supervised Visual Representation Learning

In this paper, we propose a self-supervised visual representation learni...

Yunjie Tian, et al. ∙

research

∙ 11/11/2021

On the Equivalence between Neural Network and Support Vector Machine

Recent research shows that the dynamics of an infinitely wide neural net...

Yilan Chen, et al. ∙

research

∙ 10/16/2021

Deep Active Learning by Leveraging Training Dynamics

Active learning theories and methods have been extensively studied in cl...

Haonan Wang, et al. ∙

research

∙ 10/06/2021

Long-tailed Distribution Adaptation

Recognizing images with long-tailed distributions remains a challenging ...

Zhiliang Peng, et al. ∙

research

∙ 09/17/2021

Hierarchy-Aware T5 with Path-Adaptive Mask Mechanism for Hierarchical Text Classification

Hierarchical Text Classification (HTC), which aims to predict text label...

Wei Huang, et al. ∙

research

∙ 09/08/2021

Isogeometric analysis of diffusion problems on random surfaces

In this article, we discuss the numerical solution of diffusion equation...

Wei Huang, et al. ∙

research

∙ 08/03/2021

Tutorials on Testing Neural Networks

Deep learning achieves remarkable performance on pattern recognition, bu...

Nicolas Berthier, et al. ∙

research

∙ 07/31/2021

Unsupervised Cross-Modal Distillation for Thermal Infrared Tracking

The target representation learned by convolutional neural networks plays...

Jingxian Sun, et al. ∙

research

∙ 07/20/2021

Heterogeneous network-based drug repurposing for COVID-19

The Corona Virus Disease 2019 (COVID-19) belongs to human coronaviruses ...

Shuting Jin, et al. ∙

research

∙ 06/22/2021

Differentiable Architecture Search Without Training Nor Labels: A Pruning Perspective

With leveraging the weight-sharing and continuous relaxation to enable g...

Miao Zhang, et al. ∙

research

∙ 06/02/2021

Assessing the Reliability of Deep Learning Classifiers Through Robustness Evaluation and Operational Profiles

The utilisation of Deep Learning (DL) is advancing into increasingly mor...

Xingyu Zhao, et al. ∙

research

∙ 05/09/2021

Conformer: Local Features Coupling Global Representations for Visual Recognition

Within Convolutional Neural Network (CNN), the convolution operations ar...

Zhiliang Peng, et al. ∙

research

∙ 05/05/2021

PD-GAN: Probabilistic Diverse GAN for Image Inpainting

We propose PD-GAN, a probabilistic diverse GAN for image inpainting. Giv...

Hongyu Liu, et al. ∙

research

∙ 04/16/2021

Advanced Deep Networks for 3D Mitochondria Instance Segmentation

Mitochondria instance segmentation from electron microscopy (EM) images ...

Mingxing Li, et al. ∙

research

∙ 04/13/2021

Detecting Operational Adversarial Examples for Reliable Deep Learning

The utilisation of Deep Learning (DL) raises new challenges regarding it...

Xingyu Zhao, et al. ∙

research

∙ 03/24/2021

Towards Optimal Algorithms for Multi-Player Bandits without Collision Sensing Information

We propose a novel algorithm for multi-player multi-armed bandits withou...

Wei Huang, et al. ∙

research

∙ 03/23/2021

DeFLOCNet: Deep Image Editing via Flexible Low-level Controls

User-intended visual content fills the hole regions of an input image in...

Hongyu Liu, et al. ∙

research

∙ 03/12/2021

Sequential Random Network for Fine-grained Image Classification

Deep Convolutional Neural Network (DCNN) and Transformer have achieved r...

Chaorong Li, et al. ∙

research

∙ 03/03/2021

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

Graph convolutional networks (GCNs) and their variants have achieved gre...

Wei Huang, et al. ∙

research

∙ 12/18/2020

Fairness and Accuracy in Federated Learning

In the federated learning setting, multiple clients jointly train a mode...

Wei Huang, et al. ∙

research

∙ 11/25/2020

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

Correctly choosing a learning rate (scheme) for gradient-based optimizat...

Wei Huang, et al. ∙

research

∙ 10/16/2020

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...

Wei Huang, et al. ∙

research

∙ 10/16/2020

Embedding and Synthesis of Knowledge in Tree Ensemble Classifiers

This paper studies the embedding and synthesis of knowledge in tree ense...

Wei Huang, et al. ∙

research

∙ 07/14/2020

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

Deep encoder-decoder based CNNs have advanced image inpainting methods f...

Hongyu Liu, et al. ∙

research

∙ 05/19/2020

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

This paper investigates the achievable rate region of the multiple-input...

Wei Huang, et al. ∙

research

∙ 04/13/2020

On the Neural Tangent Kernel of Deep Networks with Orthogonal Initialization

In recent years, a critical initialization scheme with orthogonal initia...

Wei Huang, et al. ∙

research

∙ 12/19/2019

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

Context-aware recommender systems (CARS) have gained increasing attentio...

Wei Huang, et al. ∙

research

∙ 12/19/2019

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 ...

Wei Huang, et al. ∙

research

∙ 12/18/2019

One-Stage Inpainting with Bilateral Attention and Pyramid Filling Block

Recent deep learning based image inpainting methods which utilize contex...

Hongyu Liu, et al. ∙

research

∙ 11/05/2019

Test Metrics for Recurrent Neural Networks

Recurrent neural networks (RNNs) have been applied to a broad range of a...

Wei Huang, et al. ∙

research

∙ 10/11/2019

SoK: Hardware Security Support for Trustworthy Execution

In recent years, there have emerged many new hardware mechanisms for imp...

Lianying Zhao, et al. ∙

research

∙ 06/20/2019

testRNN: Coverage-guided Testing on Recurrent Neural Networks

Recurrent neural networks (RNNs) have been widely applied to various seq...

Wei Huang, et al. ∙

research

∙ 02/27/2019

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

Person attributes are often exploited as mid-level human semantic inform...

Shuzhao Li, et al. ∙

research

∙ 08/29/2018

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

Heterogeneous processors with architecturally different cores (CPU and G...

Kapil Dev, et al. ∙

research

∙ 05/01/2018

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

Multiobjective optimization evolutionary algorithms have been successful...

Wei Huang, et al. ∙

research

∙ 03/21/2018

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

Immersive media streaming, especially virtual reality (VR)/360-degree vi...

Wei Huang, et al. ∙

Wei Huang

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