3 papers
cs.LG2025
Conditional Hierarchical Bayesian Tucker Decomposition for Genetic Data Analysis
Adam Sandler, Diego Klabjan, Yuan Luo
We analyze large, multi-dimensional, sparse counting data sets, finding unsupervised groups to provide unique insights into genetic data. We create gene and biological pathway grou…
cs.LG2025
Non-Convex Optimization with Spectral Radius Regularization
Adam Sandler, Diego Klabjan, Yuan Luo
We develop regularization methods to find flat minima while training deep neural networks. These minima generalize better than sharp minima, yielding models outperforming baselines…
cs.CL2025
Exploring Large Language Models for Knowledge Graph Completion
Liang Yao, Jiazhen Peng, Chengsheng Mao +1
Knowledge graphs play a vital role in numerous artificial intelligence tasks, yet they frequently face the issue of incompleteness. In this study, we explore utilizing Large Langua…