b'Chao Huang'

research

∙ 06/26/2022

Cross-Silo Federated Learning: Challenges and Opportunities

Federated learning (FL) is an emerging technology that enables the train...

Chao Huang, et al. ∙

research

∙ 06/06/2022

Multi-Behavior Sequential Recommendation with Temporal Graph Transformer

Modeling time-evolving preferences of users with their sequential item i...

Lianghao Xia, et al. ∙

research

∙ 05/24/2022

RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation

Recipe recommendation systems play an essential role in helping people d...

Yijun Tian, et al. ∙

research

∙ 05/08/2022

Mutual Distillation Learning Network for Trajectory-User Linking

Trajectory-User Linking (TUL), which links trajectories to users who gen...

Wei Chen, et al. ∙

research

∙ 05/02/2022

Knowledge Graph Contrastive Learning for Recommendation

Knowledge Graphs (KGs) have been utilized as useful side information to ...

Yuhao Yang, et al. ∙

research

∙ 04/26/2022

Hypergraph Contrastive Collaborative Filtering

Collaborative Filtering (CF) has emerged as fundamental paradigms for pa...

Lianghao Xia, et al. ∙

research

∙ 04/20/2022

Scalable Motif Counting for Large-scale Temporal Graphs

One fundamental problem in temporal graph analysis is to count the occur...

Zhongqiang Gao, et al. ∙

research

∙ 04/18/2022

Spatial-Temporal Hypergraph Self-Supervised Learning for Crime Prediction

Crime has become a major concern in many cities, which calls for the ris...

Zhonghang Li, et al. ∙

research

∙ 04/15/2022

MetaSets: Meta-Learning on Point Sets for Generalizable Representations

Deep learning techniques for point clouds have achieved strong performan...

Chao Huang, et al. ∙

research

∙ 03/26/2022

Efficient Global Robustness Certification of Neural Networks via Interleaving Twin-Network Encoding

The robustness of deep neural networks has received significant interest...

Zhilu Wang, et al. ∙

research

∙ 03/08/2022

Incentivizing Data Contribution in Cross-Silo Federated Learning

In cross-silo federated learning, clients (e.g., organizations) collecti...

Chao Huang, et al. ∙

research

∙ 02/17/2022

Contrastive Meta Learning with Behavior Multiplicity for Recommendation

A well-informed recommendation framework could not only help users ident...

Wei Wei, et al. ∙

research

∙ 01/28/2022

Joint Differentiable Optimization and Verification for Certified Reinforcement Learning

In model-based reinforcement learning for safety-critical control system...

Yixuan Wang, et al. ∙

research

∙ 01/22/2022

Physics-Aware Safety-Assured Design of Hierarchical Neural Network based Planner

Neural networks have shown great promises in planning, control, and gene...

Xiangguo Liu, et al. ∙

research

∙ 01/07/2022

Spatial-Temporal Sequential Hypergraph Network for Crime Prediction

Crime prediction is crucial for public safety and resource optimization,...

Lianghao Xia, et al. ∙

research

∙ 01/07/2022

Multi-Behavior Enhanced Recommendation with Cross-Interaction Collaborative Relation Modeling

Many previous studies aim to augment collaborative filtering with deep n...

Lianghao Xia, et al. ∙

research

∙ 10/13/2021

Federated Natural Language Generation for Personalized Dialogue System

Neural conversational models have long suffered from the problem of inco...

Yujie Lu, et al. ∙

research

∙ 10/08/2021

Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks

Social recommendation which aims to leverage social connections among us...

Huance Xu, et al. ∙

research

∙ 10/08/2021

Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network

Accurate forecasting of citywide traffic flow has been playing critical ...

Xiyue Zhang, et al. ∙

research

∙ 10/08/2021

Multiplex Behavioral Relation Learning for Recommendation via Memory Augmented Transformer Network

Capturing users' precise preferences is of great importance in various r...

Lianghao Xia, et al. ∙

research

∙ 10/08/2021

Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation

Accurate user and item embedding learning is crucial for modern recommen...

Lianghao Xia, et al. ∙

research

∙ 10/08/2021

Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation

Session-based recommendation plays a central role in a wide spectrum of ...

Chao Huang, et al. ∙

research

∙ 10/08/2021

Knowledge-aware Coupled Graph Neural Network for Social Recommendation

Social recommendation task aims to predict users' preferences over items...

Chao Huang, et al. ∙

research

∙ 10/08/2021

Graph Meta Network for Multi-Behavior Recommendation

Modern recommender systems often embed users and items into low-dimensio...

Lianghao Xia, et al. ∙

research

∙ 10/08/2021

Social Recommendation with Self-Supervised Metagraph Informax Network

In recent years, researchers attempt to utilize online social informatio...

Xiaoling Long, et al. ∙

research

∙ 10/07/2021

Recent Advances in Heterogeneous Relation Learning for Recommendation

Recommender systems have played a critical role in many web applications...

Chao Huang, et al. ∙

research

∙ 06/25/2021

POLAR: A Polynomial Arithmetic Framework for Verifying Neural-Network Controlled Systems

We propose POLAR, a polynomial arithmetic framework that leverages polyn...

Chao Huang, et al. ∙

research

∙ 04/17/2021

VSpSR: Explorable Super-Resolution via Variational Sparse Representation

Super-resolution (SR) is an ill-posed problem, which means that infinite...

Hangqi Zhou, et al. ∙

research

∙ 04/15/2021

Human-in-the-Loop Deep Reinforcement Learning with Application to Autonomous Driving

Due to the limited smartness and abilities of machine intelligence, curr...

Jingda Wu, et al. ∙

research

∙ 04/09/2021

BERT-based Chinese Text Classification for Emergency Domain with a Novel Loss Function

This paper proposes an automatic Chinese text categorization method for ...

Zhongju Wang, et al. ∙

research

∙ 04/08/2021

Strategic Information Revelation in Crowdsourcing Systems Without Verification

We study a crowdsourcing problem where the platform aims to incentivize ...

Chao Huang, et al. ∙

research

∙ 04/07/2021

Synthesized Trust Learning from Limited Human Feedback for Human-Load-Reduced Multi-Robot Deployments

Human multi-robot system (MRS) collaboration is demonstrating potentials...

Yijiang Pang, et al. ∙

research

∙ 03/14/2021

Repairing Human Trust by Promptly Correcting Robot Mistakes with An Attention Transfer Model

In human-robot collaboration (HRC), human trust in the robot is the huma...

Ruijiao Luo, et al. ∙

research

∙ 03/14/2021

Meta Preference Learning for Fast User Adaptation in Human-Supervisory Multi-Robot Deployments

As multi-robot systems (MRS) are widely used in various tasks such as na...

Chao Huang, et al. ∙

research

∙ 06/28/2020

Inner Attention Modeling for Flexible Teaming of Heterogeneous Multi Robots Using Multi-Agent Reinforcement Learning

With the advantages of member diversity and team scale, heterogeneous mu...

Chao Huang, et al. ∙

research

∙ 05/28/2020

Bipartite Distance for Shape-Aware Landmark Detection in Spinal X-Ray Images

Scoliosis is a congenital disease that causes lateral curvature in the s...

Abdullah-Al-Zubaer Imran, et al. ∙

research

∙ 05/22/2020

Human-Like Decision Making for Autonomous Driving: A Noncooperative Game Theoretic Approach

Considering that human-driven vehicles and autonomous vehicles (AVs) wil...

Peng Hang, et al. ∙

research

∙ 05/22/2020

An Integrated Framework of Decision Making and Motion Planning for Autonomous Vehicles Considering Social Behaviors

This paper presents a novel integrated approach to deal with the decisio...

Peng Hang, et al. ∙

research

∙ 05/05/2020

Partly Supervised Multitask Learning

Semi-supervised learning has recently been attracting attention as an al...

Abdullah-Al-Zubaer Imran, et al. ∙

research

∙ 04/15/2020

Analysis of Scoliosis From Spinal X-Ray Images

Scoliosis is a congenital disease in which the spine is deformed from it...

Abdullah-Al-Zubaer Imran, et al. ∙

research

∙ 03/14/2020

Non-Local Part-Aware Point Cloud Denoising

This paper presents a novel non-local part-aware deep neural network to ...

Chao Huang, et al. ∙

research

∙ 02/12/2020

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...

Chao Huang, et al. ∙

research

∙ 02/10/2020

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

The prevalence of wearable sensors (e.g., smart wristband) is enabling a...

Xian Wu, et al. ∙

research

∙ 12/09/2019

Shape-Aware Organ Segmentation by Predicting Signed Distance Maps

In this work, we propose to resolve the issue existing in current deep l...

Yuan Xue, et al. ∙

research

∙ 11/26/2019

Few-Shot Knowledge Graph Completion

Knowledge graphs (KGs) serve as useful resources for various natural lan...

Chuxu Zhang, et al. ∙

research

∙ 11/19/2019

Heterogeneous Deep Graph Infomax

Graph representation learning is to learn universal node representations...

Yuxiang Ren, et al. ∙

research

∙ 08/19/2019

Graph Fourier Transform Based on ℓ_1 Norm Variation Minimization

The definition of the graph Fourier transform is a fundamental issue in ...

Lihua Yang, et al. ∙

research

∙ 06/25/2019

ReachNN: Reachability Analysis of Neural-Network Controlled Systems

Applying neural networks as controllers in dynamical systems has shown g...

Chao Huang, et al. ∙

research

∙ 05/09/2019

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

In the path planning problem of autonomous application, the existing stu...

Chao Huang, et al. ∙

research

∙ 04/08/2019

Extreme Image Compression via Multiscale Autoencoders With Generative Adversarial Optimization

We propose a MultiScale AutoEncoder(MSAE) based extreme image compressio...

Chao Huang, et al. ∙

Chao Huang

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