collaborators

6 papers

cs.RO2026

Quasi-Periodic Gaussian Process Predictive Iterative Learning Control

Unnati Nigam, Radhendushka Srivastava, Faezeh Marzbanrad +1

Repetitive motion tasks are common in robotics, but performance can degrade over time due to environmental changes and robot wear and tear. Iterative learning control (ILC) improve…

stat.AP2026

Correction of Pooling Matrix Mis-specifications in Compressed Sensing Based Group Testing

Shuvayan Banerjee, Radhendushka Srivastava, James Saunderson +1

Compressed sensing, which involves the reconstruction of sparse signals from an under-determined linear system, has been recently used to solve problems in group testing. In a publ…

stat.ME2025

A structural equation formulation for general quasi-periodic Gaussian processes

Unnati Nigam, Radhendushka Srivastava, Faezeh Marzbanrad +1

This paper introduces a structural equation formulation that gives rise to a new family of quasi-periodic Gaussian processes, useful to process a broad class of natural and physiol…

stat.ME2025

A semi-parametric model for assessing the effect of temperature on ice accumulation rate from Antarctic ice core data

Radhendushka Srivastava, Debasis Sengupta

In this paper, we present a semiparametric model for describing the effect of temperature on Antarctic ice accumulation on a paleoclimatic time scale. The model is motivated by sha…

stat.ML2025

Robust Non-adaptive Group Testing under Errors in Group Membership Specifications

Shuvayan Banerjee, Radhendushka Srivastava, James Saunderson +1

Given samples, each of which may or may not be defective, group testing (GT) aims to determine their defect status by performing tests on `groups', where a group is for…

stat.ML2025

Fast Debiasing of the LASSO Estimator

Shuvayan Banerjee, James Saunderson, Radhendushka Srivastava +1

In high-dimensional sparse regression, the \textsc{Lasso} estimator offers excellent theoretical guarantees but is well-known to produce biased estimates. To address this, \cite{Ja…