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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...
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08/20/2023
StableLLaVA: Enhanced Visual Instruction Tuning with Synthesized Image-Dialogue Data
The remarkable multimodal capabilities demonstrated by OpenAI's GPT-4 ha...
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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...
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07/02/2023
DSTCGCN: Learning Dynamic Spatial-Temporal Cross Dependencies for Traffic Forecasting
Traffic forecasting is essential to intelligent transportation systems, ...
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05/18/2023
CHBias: Bias Evaluation and Mitigation of Chinese Conversational Language Models
Warning: This paper contains content that may be offensive or upsetting....
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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...
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04/26/2023
Towards Medical Artificial General Intelligence via Knowledge-Enhanced Multimodal Pretraining
Medical artificial general intelligence (MAGI) enables one foundation mo...
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04/03/2023
Disentangled Pre-training for Image Matting
Image matting requires high-quality pixel-level human annotations to sup...
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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...
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02/22/2023
GTRL: An Entity Group-Aware Temporal Knowledge Graph Representation Learning Method
Temporal Knowledge Graph (TKG) representation learning embeds entities a...
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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...
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08/05/2022
Dynamic Adaptive and Adversarial Graph Convolutional Network for Traffic Forecasting
Traffic forecasting is challenging due to dynamic and complicated spatia...
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05/29/2022
Diminishing Empirical Risk Minimization for Unsupervised Anomaly Detection
Unsupervised anomaly detection (AD) is a challenging task in realistic a...
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05/21/2022
Temporal Domain Generalization with Drift-Aware Dynamic Neural Network
Temporal domain generalization is a promising yet extremely challenging ...
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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...
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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...
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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 ...
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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...
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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...
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12/14/2021
Scale-Aware Neural Architecture Search for Multivariate Time Series Forecasting
Multivariate time series (MTS) forecasting has attracted much attention ...
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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...
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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) ...
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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...
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10/09/2021
Multi-Relation Aware Temporal Interaction Network Embedding
Temporal interaction networks are formed in many fields, e.g., e-commerc...
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09/21/2021
Generalization in Text-based Games via Hierarchical Reinforcement Learning
Deep reinforcement learning provides a promising approach for text-based...
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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...
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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...
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04/05/2021
DexDeepFM: Ensemble Diversity Enhanced Extreme Deep Factorization Machine Model
Predicting user positive response (e.g., purchases and clicks) probabili...
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03/21/2021
Homophily Outlier Detection in Non-IID Categorical Data
Most of existing outlier detection methods assume that the outlier facto...
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03/05/2021
Unified Robust Training for Graph NeuralNetworks against Label Noise
Graph neural networks (GNNs) have achieved state-of-the-art performance ...
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03/03/2021
Wide Graph Neural Networks: Aggregation Provably Leads to Exponentially Trainability Loss
Graph convolutional networks (GCNs) and their variants have achieved gre...
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01/12/2021
HighAir: A Hierarchical Graph Neural Network-Based Air Quality Forecasting Method
Accurately forecasting air quality is critical to protecting general pub...
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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...
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02/25/2020
Smoothing Graphons for Modelling Exchangeable Relational Data
Modelling exchangeable relational data can be described by graphon theor...
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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...
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01/13/2020
Relational State-Space Model for Stochastic Multi-Object Systems
Real-world dynamical systems often consist of multiple stochastic subsys...
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11/27/2019
Multi-Range Attentive Bicomponent Graph Convolutional Network for Traffic Forecasting
Traffic forecasting is of great importance to transportation management ...
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11/04/2019
Scalable Deep Generative Relational Models with High-Order Node Dependence
We propose a probabilistic framework for modelling and exploring the lat...
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08/22/2019
Semi-supervised Adversarial Active Learning on Attributed Graphs
Active learning (AL) on attributed graphs has received increasing attent...
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11/12/2018
A Review for Weighted MinHash Algorithms
Data similarity (or distance) computation is a fundamental research topi...
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09/30/2018
Privacy-preserving Stochastic Gradual Learning
It is challenging for stochastic optimizations to handle large-scale sen...
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06/13/2018
Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection
Learning expressive low-dimensional representations of ultrahigh-dimensi...
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11/03/2016