6 papers
A Resilience Framework for Bi-Criteria Combinatorial Optimization with Bandit Feedback
Vaneet Aggarwal, Shweta Jain, Subham Pokhriyal +1
We study bi-criteria combinatorial optimization under noisy function evaluations. While resilience and black-box offline-to-online reductions have been studied in single-objective…
Meritocratic Fairness via -Shapley Values in Budgeted Combinatorial Bandits with Full-Bandit Feedback
Shradha Sharma, Swapnil Dhamal, Shweta Jain
We study meritocratic fairness in budgeted combinatorial multi-armed bandits with full-bandit feedback, where a learner selects at most arms per time step and observes only the…
Lipschitz Dueling Bandits over Continuous Action Spaces
Mudit Sharma, Shweta Jain, Vaneet Aggarwal +1
We study for the first time, stochastic dueling bandits over continuous action spaces with Lipschitz structure, where feedback is purely comparative. While dueling bandits and Lips…
Multi-Agent Combinatorial-Multi-Armed-Bandit framework for the Submodular Welfare Problem under Bandit Feedback
Subham Pokhriyal, Shweta Jain, Vaneet Aggarwal
We study the \emph{Submodular Welfare Problem} (SWP), where items are partitioned among agents with monotone submodular utilities to maximize the total welfare under \emph{bandit f…
The Multi-Stage Assignment Problem: A Fairness Perspective
Vibulan J, Swapnil Dhamal, Shweta Jain
This paper explores the problem of fair assignment on Multi-Stage graphs. A multi-stage graph consists of nodes partitioned into disjoint sets (stages) structured as a sequence…
Towards Fairness in Provably Communication-Efficient Federated Recommender Systems
Kirandeep Kaur, Sujit Gujar, Shweta Jain
To reduce the communication overhead caused by parallel training of multiple clients, various federated learning (FL) techniques use random client sampling. Nonetheless, ensuring t…