5 papers
Learning Mixtures of Nonparametric and Convolutional Measures on Effectively Low-dimensional Affine Spaces
Sunrit Chakraborty, XuanLong Nguyen
In this paper, we develop a finite mixture of convolutional distributions, a statistical model to analyze continuous data distributed approximately on a mixture of low-dimensional…
From Collapse to Improvement: Statistical Perspectives on the Evolutionary Dynamics of Iterative Training on Contaminated Sources
Soham Bakshi, Sunrit Chakraborty
The problem of model collapse has presented new challenges in iterative training of generative models, where such training with synthetic data leads to an overall degradation of pe…
Dirichlet moment tensors and the correspondence between admixture and mixture of product models
Dat Do, Sunrit Chakraborty, Jonathan Terhorst +1
Understanding posterior contraction behavior in Bayesian hierarchical models is of fundamental importance, but progress in this question is relatively sparse in comparison to the t…
FLIPHAT: Joint Differential Privacy for High Dimensional Sparse Linear Bandits
Sunrit Chakraborty, Saptarshi Roy, Debabrota Basu
High dimensional sparse linear bandits serve as an efficient model for sequential decision-making problems (e.g. personalized medicine), where high dimensional features (e.g. genom…
Learning Topic Hierarchies by Tree-Directed Latent Variable Models
Sunrit Chakraborty, Rayleigh Lei, XuanLong Nguyen
We study a parametric family of latent variable models, namely topic models, equipped with a hierarchical structure among the topic variables. Such models may be viewed as a finite…