9 citations · 15 across the 12 of their papers we have counts for
15 papers
Robust Detection of LLM-Generated Text under Contamination
Jiaxun Li, Saptarshi Chakraborty, Ambuj Tewari
We study the detection of LLM-generated text under editing and contamination. Modeling human and machine text as finite-order Markov processes with Huber contamination, we characte…
Convex Clustering Redefined: Robust Learning with the Median of Means Estimator
Sourav De, Koustav Chowdhury, Bibhabasu Mandal +4
Clustering approaches that utilize convex loss functions have recently attracted growing interest in the formation of compact data clusters. Although classical methods like k-means…
A New Framework for Convex Clustering in Kernel Spaces: Finite Sample Bounds, Consistency and Performance Insights
Shubhayan Pan, Kushal Bose, Debolina Paul +2
Convex clustering is a well-regarded clustering method, resembling the similar centroid-based approach of Lloyd's -means, without requiring a predefined cluster count. It starts…
Topical Hidden Genome: Discovering Latent Cancer Mutational Topics using a Bayesian Multilevel Context-learning Approach
Saptarshi Chakraborty, Zoe Guan, Colin B. Begg +1
Statistical inference on the cancer-site specificities of collective ultra-rare whole genome somatic mutations is an open problem. Traditional statistical methods cannot handle who…
Bregman Power k-Means for Clustering Exponential Family Data
Adithya Vellal, Saptarshi Chakraborty, Jason Xu
Recent progress in center-based clustering algorithms combats poor local minima by implicit annealing, using a family of generalized means. These methods are variations of Lloyd's…
Robust Linear Predictions: Analyses of Uniform Concentration, Fast Rates and Model Misspecification
Saptarshi Chakraborty, Debolina Paul, Swagatam Das
The problem of linear predictions has been extensively studied for the past century under pretty generalized frameworks. Recent advances in the robust statistics literature allow u…