12 citations · 28 across the 13 of their papers we have counts for
13 papers
LLmFPCA-detect: LLM-powered Multivariate Functional PCA for Anomaly Detection in Sparse Longitudinal Texts
Prasanjit Dubey, Aritra Guha, Zhengyi Zhou +3
Sparse longitudinal (SL) textual data arises when individuals generate text repeatedly over time (e.g., customer reviews, occasional social media posts, electronic medical records…
A Bayesian approach to learning mixtures of nonparametric components
Yilei Zhang, Yun Wei, Aritra Guha +1
Mixture models are widely used in modeling heterogeneous data populations. A standard approach of mixture modeling assumes that the mixture component takes a parametric kernel form…
Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics
Jiacheng Zhu, Jielin Qiu, Aritra Guha +4
We propose to study and promote the robustness of a model as per its performance through the interpolation of training data distributions. Specifically, (1) we augment the data by…
On Excess Mass Behavior in Gaussian Mixture Models with Orlicz-Wasserstein Distances
Aritra Guha, Nhat Ho, XuanLong Nguyen
Dirichlet Process mixture models (DPMM) in combination with Gaussian kernels have been an important modeling tool for numerous data domains arising from biological, physical, and s…
Towards Algorithmic Fairness in Space-Time: Filling in Black Holes
Cheryl Flynn, Aritra Guha, Subhabrata Majumdar +2
New technologies and the availability of geospatial data have drawn attention to spatio-temporal biases present in society. For example: the COVID-19 pandemic highlighted dispariti…
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…
Functional optimal transport: map estimation and domain adaptation for functional data
Jiacheng Zhu, Aritra Guha, Dat Do +3
We introduce a formulation of optimal transport problem for distributions on function spaces, where the stochastic map between functional domains can be partially represented in te…
Outlier-Robust Optimal Transport
Debarghya Mukherjee, Aritra Guha, Justin Solomon +2
Optimal transport (OT) measures distances between distributions in a way that depends on the geometry of the sample space. In light of recent advances in computational OT, OT dista…
Robust Unsupervised Learning of Temporal Dynamic Interactions
Aritra Guha, Rayleigh Lei, Jiacheng Zhu +2
Robust representation learning of temporal dynamic interactions is an important problem in robotic learning in general and automated unsupervised learning in particular. Temporal d…
Dirichlet Simplex Nest and Geometric Inference
Mikhail Yurochkin, Aritra Guha, Yuekai Sun +1
We propose Dirichlet Simplex Nest, a class of probabilistic models suitable for a variety of data types, and develop fast and provably accurate inference algorithms by accounting f…
On posterior contraction of parameters and interpretability in Bayesian mixture modeling
Aritra Guha, Nhat Ho, XuanLong Nguyen
We study posterior contraction behaviors for parameters of interest in the context of Bayesian mixture modeling, where the number of mixing components is unknown while the model it…
Scalable inference of topic evolution via models for latent geometric structures
Mikhail Yurochkin, Zhiwei Fan, Aritra Guha +2
We develop new models and algorithms for learning the temporal dynamics of the topic polytopes and related geometric objects that arise in topic model based inference. Our model is…
Conic Scan-and-Cover algorithms for nonparametric topic modeling
Mikhail Yurochkin, Aritra Guha, XuanLong Nguyen
We propose new algorithms for topic modeling when the number of topics is unknown. Our approach relies on an analysis of the concentration of mass and angular geometry of the topic…