87 citations · 166 across the 13 of their papers we have counts for
14 papers
Context-Aware Clustering using Large Language Models
Sindhu Tipirneni, Ravinarayana Adkathimar, Nurendra Choudhary +5
Despite the remarkable success of Large Language Models (LLMs) in text understanding and generation, their potential for text clustering tasks remains underexplored. We observed th…
Geometric Matrix Completion via Sylvester Multi-Graph Neural Network
Boxin Du, Changhe Yuan, Fei Wang +1
Despite the success of the Sylvester equation empowered methods on various graph mining applications, such as semi-supervised label learning and network alignment, there also exist…
Hypergraph Pre-training with Graph Neural Networks
Boxin Du, Changhe Yuan, Robert Barton +2
Despite the prevalence of hypergraphs in a variety of high-impact applications, there are relatively few works on hypergraph representation learning, most of which primarily focus…
Graph Neural Networks for Inconsistent Cluster Detection in Incremental Entity Resolution
Robert A. Barton, Tal Neiman, Changhe Yuan
Online stores often utilize product relationships such as bundles and substitutes to improve their catalog quality and guide customers through myriad choices. Entity resolution usi…
Most Relevant Explanation in Bayesian Networks
Changhe Yuan, Heejin Lim, Tsai-Ching Lu
A major inference task in Bayesian networks is explaining why some variables are observed in their particular states using a set of target variables. Existing methods for solving t…
Evaluating Anytime Algorithms for Learning Optimal Bayesian Networks
Brandon Malone, Changhe Yuan
Exact algorithms for learning Bayesian networks guarantee to find provably optimal networks. However, they may fail in difficult learning tasks due to limited time or memory. In th…