b'Ling Chen'

research

∙ 08/29/2023

ABS-SGD: A Delayed Synchronous Stochastic Gradient Descent Algorithm with Adaptive Batch Size for Heterogeneous GPU Clusters

As the size of models and datasets grows, it has become increasingly com...

0 Xin Zhou, et al. ∙

research

∙ 08/20/2023

StableLLaVA: Enhanced Visual Instruction Tuning with Synthesized Image-Dialogue Data

The remarkable multimodal capabilities demonstrated by OpenAI's GPT-4 ha...

0 Yanda Li, et al. ∙

research

∙ 07/07/2023

CSCLog: A Component Subsequence Correlation-Aware Log Anomaly Detection Method

Anomaly detection based on system logs plays an important role in intell...

0 Ling Chen, et al. ∙

research

∙ 07/02/2023

DSTCGCN: Learning Dynamic Spatial-Temporal Cross Dependencies for Traffic Forecasting

Traffic forecasting is essential to intelligent transportation systems, ...

0 Binqing Wu, et al. ∙

research

∙ 05/18/2023

CHBias: Bias Evaluation and Mitigation of Chinese Conversational Language Models

Warning: This paper contains content that may be offensive or upsetting....

7 Jiaxu Zhao, et al. ∙

research

∙ 05/04/2023

A Spectral Method for Identifiable Grade of Membership Analysis with Binary Responses

Grade of Membership (GoM) models are popular individual-level mixture mo...

0 Ling Chen, et al. ∙

research

∙ 04/26/2023

Towards Medical Artificial General Intelligence via Knowledge-Enhanced Multimodal Pretraining

Medical artificial general intelligence (MAGI) enables one foundation mo...

17 Bingqian Lin, et al. ∙

research

∙ 04/03/2023

Disentangled Pre-training for Image Matting

Image matting requires high-quality pixel-level human annotations to sup...

0 Yanda Li, et al. ∙

research

∙ 03/09/2023

SLCA: Slow Learner with Classifier Alignment for Continual Learning on a Pre-trained Model

The goal of continual learning is to improve the performance of recognit...

0 Gengwei Zhang, et al. ∙

research

∙ 02/22/2023

GTRL: An Entity Group-Aware Temporal Knowledge Graph Representation Learning Method

Temporal Knowledge Graph (TKG) representation learning embeds entities a...

0 Xing Tang, et al. ∙

research

∙ 12/31/2022

Hospital transfer risk prediction for COVID-19 patients from a medicalized hotel based on Diffusion GraphSAGE

The global COVID-19 pandemic has caused more than six million deaths wor...

0 Jun-En Ding, et al. ∙

research

∙ 08/05/2022

Dynamic Adaptive and Adversarial Graph Convolutional Network for Traffic Forecasting

Traffic forecasting is challenging due to dynamic and complicated spatia...

0 Juyong Jiang, et al. ∙

research

∙ 05/29/2022

Diminishing Empirical Risk Minimization for Unsupervised Anomaly Detection

Unsupervised anomaly detection (AD) is a challenging task in realistic a...

0 Shaoshen Wang, et al. ∙

research

∙ 05/21/2022

Temporal Domain Generalization with Drift-Aware Dynamic Neural Network

Temporal domain generalization is a promising yet extremely challenging ...

1 Guangji Bai, et al. ∙

research

∙ 04/21/2022

Is Neural Topic Modelling Better than Clustering? An Empirical Study on Clustering with Contextual Embeddings for Topics

Recent work incorporates pre-trained word embeddings such as BERT embedd...

0 Zihan Zhang, et al. ∙

research

∙ 02/13/2022

Fine-Grained Population Mobility Data-Based Community-Level COVID-19 Prediction Model

Predicting the number of infections in the anti-epidemic process is extr...

0 Pengyue Jia, et al. ∙

research

∙ 01/20/2022

Informative Pseudo-Labeling for Graph Neural Networks with Few Labels

Graph Neural Networks (GNNs) have achieved state-of-the-art results for ...

0 Yayong Li, et al. ∙

research

∙ 01/17/2022

Rethinking Activity Awareness: The Design, Evaluation Implication of Integrating Activity Awareness into Mobile Messaging

Nowadays, different types of context information are integrated into mob...

0 Ling Chen, et al. ∙

research

∙ 01/13/2022

Multi-Scale Adaptive Graph Neural Network for Multivariate Time Series Forecasting

Multivariate time series (MTS) forecasting plays an important role in th...

0 Ling Chen, et al. ∙

research

∙ 12/14/2021

Scale-Aware Neural Architecture Search for Multivariate Time Series Forecasting

Multivariate time series (MTS) forecasting has attracted much attention ...

0 Donghui Chen, et al. ∙

research

∙ 11/09/2021

Learning from Multiple Time Series: A Deep Disentangled Approach to Diversified Time Series Forecasting

Time series forecasting is a significant problem in many applications, e...

0 Ling Chen, et al. ∙

research

∙ 11/01/2021

RMNA: A Neighbor Aggregation-Based Knowledge Graph Representation Learning Model Using Rule Mining

Although the state-of-the-art traditional representation learning (TRL) ...

0 Ling Chen, et al. ∙

research

∙ 10/26/2021

TME-BNA: Temporal Motif-Preserving Network Embedding with Bicomponent Neighbor Aggregation

Evolving temporal networks serve as the abstractions of many real-life d...

0 Ling Chen, et al. ∙

research

∙ 10/09/2021

Multi-Relation Aware Temporal Interaction Network Embedding

Temporal interaction networks are formed in many fields, e.g., e-commerc...

0 Ling Chen, et al. ∙

research

∙ 09/21/2021

Generalization in Text-based Games via Hierarchical Reinforcement Learning

Deep reinforcement learning provides a promising approach for text-based...

4 Yunqiu Xu, et al. ∙

research

∙ 09/17/2021

Multi-Level Visual Similarity Based Personalized Tourist Attraction Recommendation Using Geo-Tagged Photos

Geo-tagged photo based tourist attraction recommendation can discover us...

0 Ling Chen, et al. ∙

research

∙ 08/27/2021

Group-Aware Graph Neural Network for Nationwide City Air Quality Forecasting

The problem of air pollution threatens public health. Air quality foreca...

0 Ling Chen, et al. ∙

research

∙ 04/05/2021

DexDeepFM: Ensemble Diversity Enhanced Extreme Deep Factorization Machine Model

Predicting user positive response (e.g., purchases and clicks) probabili...

0 Ling Chen, et al. ∙

research

∙ 03/21/2021

Homophily Outlier Detection in Non-IID Categorical Data

Most of existing outlier detection methods assume that the outlier facto...

22 Guansong Pang, et al. ∙

research

∙ 03/05/2021

Unified Robust Training for Graph NeuralNetworks against Label Noise

Graph neural networks (GNNs) have achieved state-of-the-art performance ...

0 Yayong 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...

7 Wei Huang, et al. ∙

research

∙ 01/12/2021

HighAir: A Hierarchical Graph Neural Network-Based Air Quality Forecasting Method

Accurately forecasting air quality is critical to protecting general pub...

8 Jiahui Xu, et al. ∙

research

∙ 10/22/2020

Deep Reinforcement Learning with Stacked Hierarchical Attention for Text-based Games

We study reinforcement learning (RL) for text-based games, which are int...

0 Yunqiu Xu, et al. ∙

research

∙ 02/25/2020

Smoothing Graphons for Modelling Exchangeable Relational Data

Modelling exchangeable relational data can be described by graphon theor...

0 Xuhui Fan, et al. ∙

research

∙ 02/24/2020

Recurrent Dirichlet Belief Networks for Interpretable Dynamic Relational Data Modelling

The Dirichlet Belief Network (DirBN) has been recently proposed as a pro...

0 Yaqiong Li, et al. ∙

research

∙ 01/13/2020

Relational State-Space Model for Stochastic Multi-Object Systems

Real-world dynamical systems often consist of multiple stochastic subsys...

0 Fan Yang, et al. ∙

research

∙ 11/27/2019

Multi-Range Attentive Bicomponent Graph Convolutional Network for Traffic Forecasting

Traffic forecasting is of great importance to transportation management ...

0 Weiqi Chen, et al. ∙

research

∙ 11/04/2019

Scalable Deep Generative Relational Models with High-Order Node Dependence

We propose a probabilistic framework for modelling and exploring the lat...

14 Xuhui Fan, et al. ∙

research

∙ 08/22/2019

Semi-supervised Adversarial Active Learning on Attributed Graphs

Active learning (AL) on attributed graphs has received increasing attent...

0 Yayong Li, et al. ∙

research

∙ 11/12/2018

A Review for Weighted MinHash Algorithms

Data similarity (or distance) computation is a fundamental research topi...

0 Wei Wu, et al. ∙

research

∙ 09/30/2018

Privacy-preserving Stochastic Gradual Learning

It is challenging for stochastic optimizations to handle large-scale sen...

0 Bo Han, et al. ∙

research

∙ 06/13/2018

Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection

Learning expressive low-dimensional representations of ultrahigh-dimensi...

0 Guansong Pang, et al. ∙

research

∙ 11/03/2016

Extracting Actionability from Machine Learning Models by Sub-optimal Deterministic Planning

A main focus of machine learning research has been improving the general...

0 Qiang Lyu, et al. ∙

Ling Chen

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