6 papers
Oracle-Robust Online Alignment for Large Language Models
Zimeng Li, Mudit Gaur, Vaneet Aggarwal
We study online alignment of large language models under misspecified preference feedback, where the observed preference oracle deviates from an ideal but unknown ground-truth orac…
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…
LiSFC-Search: Lifelong Search for Network SFC Optimization under Non-stationary Drifts
Zuyuan Zhang, Vaneet Aggarwal, Tian Lan
Edge-cloud convergence is reshaping service provisioning across 5G/6G and computing power networks (CPNs). Service function chaining (SFC) requires continuously placing and schedul…
Stronger Approximation Guarantees for Non-Monotone γ-Weakly DR-Submodular Maximization
Hareshkumar Jadav, Ranveer Singh, Vaneet Aggarwal
Maximizing submodular objectives under constraints is a fundamental problem in machine learning and optimization. We study the maximization of a nonnegative, non-monotone -weakl…
Decentralized Projection-free Online Upper-Linearizable Optimization with Applications to DR-Submodular Optimization
Yiyang Lu, Mohammad Pedramfar, Vaneet Aggarwal
We introduce a novel framework for decentralized projection-free optimization, extending projection-free methods to a broader class of upper-linearizable functions. Our approach le…
Stochastic -Submodular Bandits with Full Bandit Feedback
Guanyu Nie, Vaneet Aggarwal, Christopher John Quinn
In this paper, we present the first sublinear -regret bounds for online -submodular optimization problems with full-bandit feedback, where is a corresponding offline appr…