8 citations · 8 across the 3 of their papers we have counts for
3 papers
stat.ME2026
Regularization in Paired Comparison Models via Pseudo-Games and Phantom Players
Mark E. Glickman
Paired comparison models are useful for estimating latent abilities or preferences from binary outcomes, but maximum likelihood estimation can be unstable or fail when the comparis…
stat.AP2026
Come Together: Analyzing Popular Songs Through Statistical Embeddings
Matthew Esmaili Mallory, Mark Glickman, Jason Brown
Statistical modeling of popular music presents a unique challenge due to the complexity of song structures, which cannot be easily analyzed using conventional statistical tools. Ho…
cs.CL2024★ 8 cited
AI and Generative AI for Research Discovery and Summarization
Mark Glickman, Yi Zhang
AI and generative AI tools, including chatbots like ChatGPT that rely on large language models (LLMs), have burst onto the scene this year, creating incredible opportunities to inc…