7 citations · 18 across the 16 of their papers we have counts for
15 papers · 1 filter
Stochastic Multi-Armed Bandits with Limited Control Variates
Arun Verma, Manjesh Kumar Hanawal, Arun Rajkumar
Motivated by wireless networks where interference or channel state estimates provide partial insight into throughput, we study a variant of the classical stochastic multi-armed ban…
Synopsis: Sequential Decision Problems with Weak Feedback
Arun Verma
This thesis considers sequential decision problems, where the loss/reward incurred by selecting an action may not be inferred from observed feedback. A major part of this thesis fo…
Sequential Decision Problems with Weak Feedback
Arun Verma
This thesis considers sequential decision problems, where the loss/reward incurred by selecting an action may not be inferred from observed feedback. A major part of this thesis fo…
Bayesian Optimization under Stochastic Delayed Feedback
Arun Verma, Zhongxiang Dai, Bryan Kian Hsiang Low
Bayesian optimization (BO) is a widely-used sequential method for zeroth-order optimization of complex and expensive-to-compute black-box functions. The existing BO methods assume…
Application of Clustering Algorithms for Dimensionality Reduction in Infrastructure Resilience Prediction Models
Srijith Balakrishnan, Beatrice Cassottana, Arun Verma
Recent studies increasingly adopt simulation-based machine learning (ML) models to analyze critical infrastructure system resilience. For realistic applications, these ML models co…
Federated Neural Bandits
Zhongxiang Dai, Yao Shu, Arun Verma +3
Recent works on neural contextual bandits have achieved compelling performances due to their ability to leverage the strong representation power of neural networks (NNs) for reward…
Stochastic Multi-Armed Bandits with Control Variates
Arun Verma, Manjesh K. Hanawal
This paper studies a new variant of the stochastic multi-armed bandits problem where auxiliary information about the arm rewards is available in the form of control variates. In ma…
Censored Semi-Bandits for Resource Allocation
Arun Verma, Manjesh K. Hanawal, Arun Rajkumar +1
We consider the problem of sequentially allocating resources in a censored semi-bandits setup, where the learner allocates resources at each step to the arms and observes loss. The…
Online Algorithm for Unsupervised Sequential Selection with Contextual Information
Arun Verma, Manjesh K. Hanawal, Csaba Szepesvári +1
In this paper, we study Contextual Unsupervised Sequential Selection (USS), a new variant of the stochastic contextual bandits problem where the loss of an arm cannot be inferred f…
Thompson Sampling for Unsupervised Sequential Selection
Arun Verma, Manjesh K. Hanawal, Nandyala Hemachandra
Thompson Sampling has generated significant interest due to its better empirical performance than upper confidence bound based algorithms. In this paper, we study Thompson Sampling…
Stochastic Network Utility Maximization with Unknown Utilities: Multi-Armed Bandits Approach
Arun Verma, Manjesh K. Hanawal
In this paper, we study a novel Stochastic Network Utility Maximization (NUM) problem where the utilities of agents are unknown. The utility of each agent depends on the amount of…
Learning and Fairness in Energy Harvesting: A Maximin Multi-Armed Bandits Approach
Debamita Ghosh, Arun Verma, Manjesh K. Hanawal
Recent advances in wireless radio frequency (RF) energy harvesting allows sensor nodes to increase their lifespan by remotely charging their batteries. The amount of energy harvest…
Unsupervised Online Feature Selection for Cost-Sensitive Medical Diagnosis
Arun Verma, Manjesh K. Hanawal, Nandyala Hemachandra
In medical diagnosis, physicians predict the state of a patient by checking measurements (features) obtained from a sequence of tests, e.g., blood test, urine test, followed by inv…
Censored Semi-Bandits: A Framework for Resource Allocation with Censored Feedback
Arun Verma, Manjesh K. Hanawal, Arun Rajkumar +1
In this paper, we study censored Semi-Bandits, a novel variant of the semi-bandits problem. The learner is assumed to have a fixed amount of resources, which it allocates to the ar…
Online Algorithm for Unsupervised Sensor Selection
Arun Verma, Manjesh K. Hanawal, Csaba Szepesvári +1
In many security and healthcare systems, the detection and diagnosis systems use a sequence of sensors/tests. Each test outputs a prediction of the latent state and carries an inhe…