31 citations · 144 across the 37 of their papers we have counts for
5 papers · 1 filter
Sleeping Combinatorial Bandits
Kumar Abhishek, Ganesh Ghalme, Sujit Gujar +1
In this paper, we study an interesting combination of sleeping and combinatorial stochastic bandits. In the mixed model studied here, at each discrete time instant, an arbitrary \e…
Ballooning Multi-Armed Bandits
Ganesh Ghalme, Swapnil Dhamal, Shweta Jain +2
In this paper, we introduce Ballooning Multi-Armed Bandits (BL-MAB), a novel extension of the classical stochastic MAB model. In the BL-MAB model, the set of available arms grows (…
Achieving Fairness in the Stochastic Multi-armed Bandit Problem
Vishakha Patil, Ganesh Ghalme, Vineet Nair +1
We study an interesting variant of the stochastic multi-armed bandit problem, called the Fair-SMAB problem, where each arm is required to be pulled for at least a given fraction of…
Topic Model Based Multi-Label Classification from the Crowd
Divya Padmanabhan, Satyanath Bhat, Shirish Shevade +1
Multi-label classification is a common supervised machine learning problem where each instance is associated with multiple classes. The key challenge in this problem is learning th…
A Robust UCB Scheme for Active Learning in Regression from Strategic Crowds
Divya Padmanabhan, Satyanath Bhat, Dinesh Garg +2
We study the problem of training an accurate linear regression model by procuring labels from multiple noisy crowd annotators, under a budget constraint. We propose a Bayesian mode…