research
∙
09/07/2023
Learning Compact Compositional Embeddings via Regularized Pruning for Recommendation
Latent factor models are the dominant backbones of contemporary recommen...
share
research
∙
08/25/2023
Heterogeneous Decentralized Machine Unlearning with Seed Model Distillation
As some recent information security legislation endowed users with uncon...
research
∙
07/29/2023
Graph Condensation for Inductive Node Representation Learning
Graph neural networks (GNNs) encounter significant computational challen...
research
∙
06/17/2023
Do as I can, not as I get: Topology-aware multi-hop reasoning on multi-modal knowledge graphs
Multi-modal knowledge graph (MKG) includes triplets that consist of enti...
research
∙
06/05/2023
Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data
Graph condensation, which reduces the size of a large-scale graph by syn...
research
∙
05/14/2023
Manipulating Visually-aware Federated Recommender Systems and Its Countermeasures
Federated recommender systems (FedRecs) have been widely explored recent...
research
∙
05/01/2023
Explicit Knowledge Graph Reasoning for Conversational Recommendation
Traditional recommender systems estimate user preference on items purely...
research
∙
04/24/2023
Joint Semantic and Structural Representation Learning for Enhancing User Preference Modelling
Knowledge graphs (KGs) have become important auxiliary information for h...
research
∙
04/08/2023
DREAM: Adaptive Reinforcement Learning based on Attention Mechanism for Temporal Knowledge Graph Reasoning
Temporal knowledge graphs (TKGs) model the temporal evolution of events ...
research
∙
04/06/2023
Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures
Federated Recommender Systems (FedRecs) are considered privacy-preservin...
research
∙
03/17/2023
High Accurate and Explainable Multi-Pill Detection Framework with Graph Neural Network-Assisted Multimodal Data Fusion
Due to the significant resemblance in visual appearance, pill misuse is ...
research
∙
03/07/2023
TinyAD: Memory-efficient anomaly detection for time series data in Industrial IoT
Monitoring and detecting abnormal events in cyber-physical systems is cr...
research
∙
02/27/2023
Semantic-aware Node Synthesis for Imbalanced Heterogeneous Information Networks
Heterogeneous graph neural networks (HGNNs) have exhibited exceptional e...
research
∙
02/10/2023
Semi-decentralized Federated Ego Graph Learning for Recommendation
Collaborative filtering (CF) based recommender systems are typically tra...
research
∙
01/30/2023
On the Interaction between Node Fairness and Edge Privacy in Graph Neural Networks
Due to the emergence of graph neural networks (GNNs) and their widesprea...
research
∙
01/26/2023
Interaction-level Membership Inference Attack Against Federated Recommender Systems
The marriage of federated learning and recommender system (FedRec) has b...
research
∙
11/11/2022
Efficient Integration of Multi-Order Dynamics and Internal Dynamics in Stock Movement Prediction
Advances in deep neural network (DNN) architectures have enabled new pre...
research
∙
11/01/2022
Efficient Graph Neural Network Inference at Large Scale
Graph neural networks (GNNs) have demonstrated excellent performance in ...
research
∙
10/17/2022
Joint Multilingual Knowledge Graph Completion and Alignment
Knowledge graph (KG) alignment and completion are usually treated as two...
research
∙
09/27/2022
Efficient On-Device Session-Based Recommendation
On-device session-based recommendation systems have been achieving incre...
research
∙
09/06/2022
A Survey of Machine Unlearning
Computer systems hold a large amount of personal data over decades. On t...
research
∙
07/17/2022
Model-Agnostic and Diverse Explanations for Streaming Rumour Graphs
The propagation of rumours on social media poses an important threat to ...
research
∙
07/01/2022
Time-aware Dynamic Graph Embedding for Asynchronous Structural Evolution
Dynamic graphs refer to graphs whose structure dynamically changes over ...
research
∙
05/13/2022
Detecting Rumours with Latency Guarantees using Massive Streaming Data
Today's social networks continuously generate massive streams of data, w...
research
∙
04/06/2022
Thinking inside The Box: Learning Hypercube Representations for Group Recommendation
As a step beyond traditional personalized recommendation, group recommen...
research
∙
12/17/2021
Personalized On-Device E-health Analytics with Decentralized Block Coordinate Descent
Actuated by the growing attention to personal healthcare and the pandemi...
research
∙
12/17/2021
Link-Intensive Alignment for Incomplete Knowledge Graphs
Knowledge graph (KG) alignment - the task of recognizing entities referr...
research
∙
12/16/2021
Graph Augmentation-Free Contrastive Learning for Recommendation
Contrastive learning (CL) recently has received considerable attention i...
research
∙
10/21/2021
PipAttack: Poisoning Federated Recommender Systems forManipulating Item Promotion
Due to the growing privacy concerns, decentralization emerges rapidly in...
research
∙
05/07/2021
DA-GCN: A Domain-aware Attentive Graph Convolution Network for Shared-account Cross-domain Sequential Recommendation
Shared-account Cross-domain Sequential recommendation (SCSR) is the task...
research
∙
11/20/2019
On Node Features for Graph Neural Networks
Graph neural network (GNN) is a deep model for graph representation lear...
research
∙
11/07/2019
Sequence-Aware Factorization Machines for Temporal Predictive Analytics
In various web applications like targeted advertising and recommender sy...
research
∙
09/06/2019