1 citations · 3 across the 9 of their papers we have counts for
12 papers
Near-Optimal Regret Bounds for Monotone Stochastic Optimization under Semi-Bandit Feedback
Tao Hu, Rohan Ghuge
Stochastic optimization models sequential decision-making under uncertainty, typically assuming known input distributions. When these distributions are unknown, \citet{agarwal2026s…
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…
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…
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…
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…
Informative Path Planning with Limited Adaptivity
Rayen Tan, Rohan Ghuge, Viswanath Nagarajan
We consider the informative path planning () problem in which a robot interacts with an uncertain environment and gathers information by visiting locations. The goal…
An Asymptotically Optimal Batched Algorithm for the Dueling Bandit Problem
Arpit Agarwal, Rohan Ghuge, Viswanath Nagarajan
We study the -armed dueling bandit problem, a variation of the traditional multi-armed bandit problem in which feedback is obtained in the form of pairwise comparisons. Previous…
Batched Dueling Bandits
Arpit Agarwal, Rohan Ghuge, Viswanath Nagarajan
The -armed dueling bandit problem, where the feedback is in the form of noisy pairwise comparisons, has been widely studied. Previous works have only focused on the sequential s…
Non-Adaptive Stochastic Score Classification and Explainable Halfspace Evaluation
Rohan Ghuge, Anupam Gupta, Viswanath Nagarajan
Sequential testing problems involve a complex system with several components, each of which is "working" with some independent probability. The outcome of each component can be det…
The Power of Adaptivity for Stochastic Submodular Cover
Rohan Ghuge, Anupam Gupta, Viswanath Nagarajan
In the stochastic submodular cover problem, the goal is to select a subset of stochastic items of minimum expected cost to cover a submodular function. Solutions in this setting co…
Quasi-Polynomial Algorithms for Submodular Tree Orienteering and Other Directed Network Design Problems
Rohan Ghuge, Viswanath Nagarajan
We consider the following general network design problem on directed graphs. The input is an asymmetric metric , root , monotone submodular function $f:2^V\right…