2026
Balanced Co-Clustering of Users and Items for Embedding Table Compression in Recommender Systems
Runhao Jiang, Renchi Yang, Donghao Wu
International ACM SIGIR Conference on Research and Development in Information Retrieval 2026
BACO is presented, a fast and effective framework for compressing embedding tables that is built on the idea of exploiting collaborative signals in user-item interactions for user and item groupings, such that similar users/items share the same embeddings in the codebook.
Balanced Co-Clustering of Users and Items for Embedding Table Compression in Recommender Systems
Runhao Jiang, Renchi Yang, Donghao Wu
International ACM SIGIR Conference on Research and Development in Information Retrieval 2026
BACO is presented, a fast and effective framework for compressing embedding tables that is built on the idea of exploiting collaborative signals in user-item interactions for user and item groupings, such that similar users/items share the same embeddings in the codebook.
Effective Clustering for Large Multi-Relational Graphs
Xiaoyang Lin, Runhao Jiang, Renchi Yang
International Conference on Management of Data (SIGMOD) 2026
DEMM and DEMM+, two effective MRGC approaches to address the aforementioned limitations of existing solutions, and extend DEMM to handle attribute-less MRGs through non-trivial adaptations.
Effective Clustering for Large Multi-Relational Graphs
Xiaoyang Lin, Runhao Jiang, Renchi Yang
International Conference on Management of Data (SIGMOD) 2026
DEMM and DEMM+, two effective MRGC approaches to address the aforementioned limitations of existing solutions, and extend DEMM to handle attribute-less MRGs through non-trivial adaptations.
2025
Community-Aware Social Community Recommendation
Runhao Jiang, Renchi Yang, Wenqing Lin
International Conference on Information and Knowledge Management (CIKM) 2025
CASO is presented, a novel and effective model specially designed for social community recommendation that includes a community detection loss in the model optimization, thereby producing community-aware embeddings for communities.
Community-Aware Social Community Recommendation
Runhao Jiang, Renchi Yang, Wenqing Lin
International Conference on Information and Knowledge Management (CIKM) 2025
CASO is presented, a novel and effective model specially designed for social community recommendation that includes a community detection loss in the model optimization, thereby producing community-aware embeddings for communities.