3 citations · 3 across the 6 of their papers we have counts for
8 papers
Factor-Assisted Density Estimation: When Ambient Dimension Enables Oracle Rates
Sunrit Chakraborty, David Dunson
We study density estimation in the high-dimensional factor model, whose fixed-dimensional latent factors have an unknown smooth density. We propose factor-assisted density estimati…
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…
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…
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…
Thompson Sampling for High-Dimensional Sparse Linear Contextual Bandits
Sunrit Chakraborty, Saptarshi Roy, Ambuj Tewari
We consider the stochastic linear contextual bandit problem with high-dimensional features. We analyze the Thompson sampling algorithm using special classes of sparsity-inducing pr…
Scalable nonparametric Bayesian learning for heterogeneous and dynamic velocity fields
Sunrit Chakraborty, Aritra Guha, Rayleigh Lei +1
Analysis of heterogeneous patterns in complex spatio-temporal data finds usage across various domains in applied science and engineering, including training autonomous vehicles to…