1 citations · 1 across the 1 of their papers we have counts for
5 papers
Semi-Bandit Learning for Monotone Stochastic Optimization
Arpit Agarwal, Rohan Ghuge, Viswanath Nagarajan +1
Stochastic optimization is a widely used approach for optimization under uncertainty, where uncertain input parameters are modeled by random variables. Exact or approximation algor…
Stochastic Function Certification with Correlations
Rohan Ghuge, Jai Moondra, Mohit Singh
We study the Stochastic Boolean Function Certification (SBFC) problem, where we are given Bernoulli random variables on a ground set of elements with…
Sequential Selection with Expirations
Yihua Xu, Rohan Ghuge, Sebastian Perez-Salazar
Motivated by applications where impatience is pervasive and evaluation times are uncertain, we study a selection model where options may expire at an unknown point in time and eval…
Improved and Oracle-Efficient Online -Multicalibration
Rohan Ghuge, Vidya Muthukumar, Sahil Singla
We study \emph{online multicalibration}, a framework for ensuring calibrated predictions across multiple groups in adversarial settings, across rounds. Although online calibrat…
Single-Sample and Robust Online Resource Allocation
Rohan Ghuge, Sahil Singla, Yifan Wang
Online Resource Allocation problem is a central problem in many areas of Computer Science, Operations Research, and Economics. In this problem, we sequentially receive stochast…