KDD 2023 - Meta Graph Learning for Long-tail Recommendation

KDD 2023 - Meta Graph Learning for Long-tail Recommendation

KDD 2023 - Adaptive Graph Contrastive Learning for RecommendationПодробнее

KDD 2023 - Adaptive Graph Contrastive Learning for Recommendation

KDD 2023 - Graph-Based Model-Agnostic Data Subsampling for Recommendation SystemsПодробнее

KDD 2023 - Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems

KDD 2023 - Learning Strong Graph Neural Networks with Weak InformationПодробнее

KDD 2023 - Learning Strong Graph Neural Networks with Weak Information

KDD 2023 - Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN)Подробнее

KDD 2023 - Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN)

KDD 2023 - Enhancing Graph Representations Learning with Decorrelated PropagationПодробнее

KDD 2023 - Enhancing Graph Representations Learning with Decorrelated Propagation

KDD 2023 - Criteria Preference-Aware Light Graph Convolution Effective Multi-Criteria RecommendationПодробнее

KDD 2023 - Criteria Preference-Aware Light Graph Convolution Effective Multi-Criteria Recommendation

KDD 2023 - PGLBox: Multi-GPU Graph Learning Framework for Web-Scale RecommendationПодробнее

KDD 2023 - PGLBox: Multi-GPU Graph Learning Framework for Web-Scale Recommendation

KDD 2023 - Graph Structure Learning via Progressive StrategyПодробнее

KDD 2023 - Graph Structure Learning via Progressive Strategy

KDD 2023 - Unifying Aspect Planning, Lexical COnstraints Generating Explanations in RecommendationПодробнее

KDD 2023 - Unifying Aspect Planning, Lexical COnstraints Generating Explanations in Recommendation

KDD 2023 - Meta multi-agent exercise recommendation: A game application perspectiveПодробнее

KDD 2023 - Meta multi-agent exercise recommendation: A game application perspective

KDD 2023 - Reconsidering Learning Objectives in Unbiased RecommendationПодробнее

KDD 2023 - Reconsidering Learning Objectives in Unbiased Recommendation

Lecture 6. Personalization. Recommender Systems.Подробнее

Lecture 6. Personalization. Recommender Systems.

KDD 2023 - Universal and Generalizable Structure Learning for Graph Neural NetworksПодробнее

KDD 2023 - Universal and Generalizable Structure Learning for Graph Neural Networks

KDD 2023 - Reconstructing Graph Diffusion History from a Single SnapshoПодробнее

KDD 2023 - Reconstructing Graph Diffusion History from a Single Snapsho

KDD 2023 - What's Behind the Mask: Understanding Masked Graph Modeling for Graph AutoencodersПодробнее

KDD 2023 - What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders

KDD 2023 - Graphs, Databases and Machine LearningПодробнее

KDD 2023 - Graphs, Databases and Machine Learning

KDD 2023 - On the Predictive Power of Graph Neural NetworksПодробнее

KDD 2023 - On the Predictive Power of Graph Neural Networks