b'Chao Huang'

research

∙ 09/17/2023

Kinematics-aware Trajectory Generation and Prediction with Latent Stochastic Differential Modeling

Trajectory generation and trajectory prediction are two critical tasks f...

0 Ruochen Jiao, et al. ∙

research

∙ 09/03/2023

Multi-Relational Contrastive Learning for Recommendation

Personalized recommender systems play a crucial role in capturing users'...

0 Wei Wei, et al. ∙

research

∙ 08/23/2023

When MiniBatch SGD Meets SplitFed Learning:Convergence Analysis and Performance Evaluation

Federated learning (FL) enables collaborative model training across dist...

0 Chao Huang, et al. ∙

research

∙ 08/22/2023

How Expressive are Graph Neural Networks in Recommendation?

Graph Neural Networks (GNNs) have demonstrated superior performance on v...

0 Xuheng Cai, et al. ∙

research

∙ 08/10/2023

SSLRec: A Self-Supervised Learning Library for Recommendation

Self-supervised learning (SSL) has gained significant interest in recent...

0 Xubin Ren, et al. ∙

research

∙ 07/31/2023

DAVIS: High-Quality Audio-Visual Separation with Generative Diffusion Models

We propose DAVIS, a Diffusion model-based Audio-VIusal Separation framew...

0 Chao Huang, et al. ∙

research

∙ 07/25/2023

Feature Importance Measurement based on Decision Tree Sampling

Random forest is effective for prediction tasks but the randomness of tr...

0 Chao Huang, et al. ∙

research

∙ 07/06/2023

Knowledge Graph Self-Supervised Rationalization for Recommendation

In this paper, we introduce a new self-supervised rationalization method...

0 Yuhao Yang, et al. ∙

research

∙ 06/27/2023

FBA-Net: Foreground and Background Aware Contrastive Learning for Semi-Supervised Atrium Segmentation

Medical image segmentation of gadolinium enhancement magnetic resonance ...

0 Yunsung Chung, et al. ∙

research

∙ 06/19/2023

Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation

Spatial-temporal graph learning has emerged as a promising solution for ...

0 Qianru Zhang, et al. ∙

research

∙ 06/14/2023

SaliencyCut: Augmenting Plausible Anomalies for Open-set Fine-Grained Anomaly Detection

Open-set fine-grained anomaly detection is a challenging task that requi...

0 Jianan Ye, et al. ∙

research

∙ 06/14/2023

LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting

Traffic forecasting plays a critical role in smart city initiatives and ...

0 Xu Liu, et al. ∙

research

∙ 06/04/2023

Graph Transformer for Recommendation

This paper presents a novel approach to representation learning in recom...

0 Chaoliu Li, et al. ∙

research

∙ 05/22/2023

Denoised Self-Augmented Learning for Social Recommendation

Social recommendation is gaining increasing attention in various online ...

0 Tianle Wang, et al. ∙

research

∙ 05/18/2023

Adaptive Graph Contrastive Learning for Recommendation

Recently, graph neural networks (GNNs) have been successfully applied to...

0 Yangqin Jiang, et al. ∙

research

∙ 05/08/2023

Graph Masked Autoencoder for Sequential Recommendation

While some powerful neural network architectures (e.g., Transformer, Gra...

0 Yaowen Ye, et al. ∙

research

∙ 05/04/2023

Disentangled Contrastive Collaborative Filtering

Recent studies show that graph neural networks (GNNs) are prevalent to m...

0 Xubin Ren, et al. ∙

research

∙ 03/31/2023

POLAR-Express: Efficient and Precise Formal Reachability Analysis of Neural-Network Controlled Systems

Neural networks (NNs) playing the role of controllers have demonstrated ...

0 Yixuan Wang, et al. ∙

research

∙ 03/27/2023

Modeling Population Movements under Uncertainty at the Border in Humanitarian Crises: A Situational Analysis Tool

Humanitarian agencies must be prepared to mobilize quickly in response t...

0 Arturo de Nieves Gutierrez de Rubalcava, et al. ∙

research

∙ 03/23/2023

Egocentric Audio-Visual Object Localization

Humans naturally perceive surrounding scenes by unifying sound and sight...

0 Chao Huang, et al. ∙

research

∙ 03/21/2023

Debiased Contrastive Learning for Sequential Recommendation

Current sequential recommender systems are proposed to tackle the dynami...

0 Yuhao Yang, et al. ∙

research

∙ 03/15/2023

Graph-less Collaborative Filtering

Graph neural networks (GNNs) have shown the power in representation lear...

0 Lianghao Xia, et al. ∙

research

∙ 03/14/2023

Disentangled Graph Social Recommendation

Social recommender systems have drawn a lot of attention in many online ...

0 Lianghao Xia, et al. ∙

research

∙ 03/14/2023

Automated Self-Supervised Learning for Recommendation

Graph neural networks (GNNs) have emerged as the state-of-the-art paradi...

0 Lianghao Xia, et al. ∙

research

∙ 03/02/2023

Heterogeneous Graph Contrastive Learning for Recommendation

Graph Neural Networks (GNNs) have become powerful tools in modeling grap...

0 Mengru Chen, et al. ∙

research

∙ 02/21/2023

Multi-Modal Self-Supervised Learning for Recommendation

The online emergence of multi-modal sharing platforms (eg, TikTok, Youtu...

0 Wei Wei, et al. ∙

research

∙ 02/17/2023

Multi-Behavior Graph Neural Networks for Recommender System

Recommender systems have been demonstrated to be effective to meet user'...

0 Lianghao Xia, et al. ∙

research

∙ 02/16/2023

LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation

Graph neural network (GNN) is a powerful learning approach for graph-bas...

0 Xuheng Cai, et al. ∙

research

∙ 02/04/2023

AV-NeRF: Learning Neural Fields for Real-World Audio-Visual Scene Synthesis

Human perception of the complex world relies on a comprehensive analysis...

0 Susan Liang, et al. ∙

research

∙ 01/30/2023

Do We Really Need Graph Neural Networks for Traffic Forecasting?

Spatio-temporal graph neural networks (STGNN) have become the most popul...

0 Xu Liu, et al. ∙

research

∙ 12/07/2022

Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction

Robust prediction of citywide traffic flows at different time periods pl...

0 Jiahao Ji, et al. ∙

research

∙ 11/15/2022

Quantifying the Impact of Label Noise on Federated Learning

Federated Learning (FL) is a distributed machine learning paradigm where...

0 Shuqi Ke, et al. ∙

research

∙ 11/12/2022

Online Anomalous Subtrajectory Detection on Road Networks with Deep Reinforcement Learning

Detecting anomalous trajectories has become an important task in many lo...

0 Qianru Zhang, et al. ∙

research

∙ 10/01/2022

Diving into Unified Data-Model Sparsity for Class-Imbalanced Graph Representation Learning

Even pruned by the state-of-the-art network compression methods, Graph N...

0 Chunhui Zhang, et al. ∙

research

∙ 09/29/2022

Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments

It is quite challenging to ensure the safety of reinforcement learning (...

5 Yixuan Wang, et al. ∙

research

∙ 08/15/2022

A Tool for Neural Network Global Robustness Certification and Training

With the increment of interest in leveraging machine learning technology...

0 Zhilu Wang, et al. ∙

research

∙ 08/12/2022

Multiplex Heterogeneous Graph Convolutional Network

Heterogeneous graph convolutional networks have gained great popularity ...

0 Pengyang Yu, et al. ∙

research

∙ 08/05/2022

Localized Sparse Incomplete Multi-view Clustering

Incomplete multi-view clustering, which aims to solve the clustering pro...

1 Chengliang Liu, et al. ∙

research

∙ 07/28/2022

Self-Supervised Hypergraph Transformer for Recommender Systems

Graph Neural Networks (GNNs) have been shown as promising solutions for ...

0 Lianghao Xia, et al. ∙

research

∙ 07/12/2022

Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation

Learning dynamic user preference has become an increasingly important co...

0 Yuhao Yang, et al. ∙

research

∙ 06/26/2022

Cross-Silo Federated Learning: Challenges and Opportunities

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

0 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...

0 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...

0 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...

0 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 ...

0 Yuhao Yang, et al. ∙

research

∙ 04/26/2022

Hypergraph Contrastive Collaborative Filtering

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

0 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...

0 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...

0 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...

5 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...

0 Zhilu Wang, et al. ∙

Chao Huang

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