8 papers
Fast segmentation of watermarked texts from large language models through an epidemic change-point framework
Soham Bonnerjee, Subhrajyoty Roy, Sayar Karmakar
With the growing use of large language models, concerns over content authenticity have spurred a variety of watermarking schemes. These schemes use secret keys to detect machine-ge…
Characterization of Generalized Alpha-Beta Divergence and Associated Entropy Measures
Subhrajyoty Roy, Supratik Basu, Abhik Ghosh +1
Minimum divergence estimators provide a natural framework for robust (parametric) statistical inference. Useful properties of several such divergence measures, including, the Helli…
Universally Optimal Robustness-Efficiency Tradeoffs for a General Class of Minimum Divergence Estimators
Subhrajyoty Roy, Supratik Basu, Abhik Ghosh +1
Balancing the efficiency of an estimator under ideal conditions against its robustness under contamination remains a central challenge in robust statistics. While minimum divergenc…
BOOOM: Loss-Function-Agnostic Black-Box Optimization over Orthonormal Manifolds for Machine Learning and Statistical Inference
Beomchang Kim, Subhrajyoty Roy, Priyam Das
Optimization over the Stiefel manifold , the set of column-orthonormal matrices, is fundamental in statistics, machine learning, and scientific compu…
Nonparametric regression of spatio-temporal data using infinite-dimensional covariates
Subhrajyoty Roy, Soudeep Deb, Sayar Karmakar +1
In spatio-temporal analysis, we often record data at specific time intervals but with varying spatial locations between these timepoints. We propose a conditional model to analyze…
Robust Rank Estimation for Noisy Matrices
Subhrajyoty Roy, Abhik Ghosh, Ayanendranath Basu
Estimating the true rank of a noisy data matrix is a fundamental problem underlying techniques such as principal component analysis, matrix completion, etc. Existing rank estimatio…