
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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RMNA: A Neighbor AggregationBased Knowledge Graph Representation Learning Model Using Rule Mining
Although the stateoftheart traditional representation learning (TRL) ...
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TMEBNA: Temporal MotifPreserving Network Embedding with Bicomponent Neighbor Aggregation
Evolving temporal networks serve as the abstractions of many reallife d...
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MultiRelation Aware Temporal Interaction Network Embedding
Temporal interaction networks are formed in many fields, e.g., ecommerc...
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Generalization in Textbased Games via Hierarchical Reinforcement Learning
Deep reinforcement learning provides a promising approach for textbased...
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MultiLevel Visual Similarity Based Personalized Tourist Attraction Recommendation Using GeoTagged Photos
Geotagged photo based tourist attraction recommendation can discover us...
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GroupAware Graph Neural Network for Nationwide City Air Quality Forecasting
The problem of air pollution threatens public health. Air quality foreca...
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DexDeepFM: Ensemble Diversity Enhanced Extreme Deep Factorization Machine Model
Predicting user positive response (e.g., purchases and clicks) probabili...
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Homophily Outlier Detection in NonIID Categorical Data
Most of existing outlier detection methods assume that the outlier facto...
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Unified Robust Training for Graph NeuralNetworks against Label Noise
Graph neural networks (GNNs) have achieved stateoftheart performance ...
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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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HighAir: A Hierarchical Graph Neural NetworkBased Air Quality Forecasting Method
Accurately forecasting air quality is critical to protecting general pub...
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Deep Reinforcement Learning with Stacked Hierarchical Attention for Textbased Games
We study reinforcement learning (RL) for textbased games, which are int...
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Smoothing Graphons for Modelling Exchangeable Relational Data
Modelling exchangeable relational data can be described by graphon theor...
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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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Relational StateSpace Model for Stochastic MultiObject Systems
Realworld dynamical systems often consist of multiple stochastic subsys...
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MultiRange Attentive Bicomponent Graph Convolutional Network for Traffic Forecasting
Traffic forecasting is of great importance to transportation management ...
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Scalable Deep Generative Relational Models with HighOrder Node Dependence
We propose a probabilistic framework for modelling and exploring the lat...
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Semisupervised Adversarial Active Learning on Attributed Graphs
Active learning (AL) on attributed graphs has received increasing attent...
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A Review for Weighted MinHash Algorithms
Data similarity (or distance) computation is a fundamental research topi...
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Privacypreserving Stochastic Gradual Learning
It is challenging for stochastic optimizations to handle largescale sen...
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Learning Representations of Ultrahighdimensional Data for Random Distancebased Outlier Detection
Learning expressive lowdimensional representations of ultrahighdimensi...
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Extracting Actionability from Machine Learning Models by Suboptimal Deterministic Planning
A main focus of machine learning research has been improving the general...
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Ling Chen
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