The research group at University of Texas at Austin published a paper titled "Convergence Rates for Latent Mixing Measures in Infinite Homoscedastic Location-Scale Mixture Models" last week on the arXiv platform.
The study focuses on the problem of information limits in Bayesian nonparametrics. Dung, currently a second-year PhD student at the university, is the lead co-author under the supervision of Ho Pham Minh Nhat, an associate professor there.
Le Quang Dung, a PhD student at the University of Texas. Photo courtesy of Dung
The paper is the first in a planned series of 10 studies aimed at fully resolving a major open problem in Bayesian nonparametrics dating back to the 1970s.
"This research uses tools from pure mathematics, but it is crucial for understanding models used in statistics. Solving this problem could lead to many other interesting results," Dung said.
