5 papers
Multi-User mmWave Beam and Rate Adaptation via Combinatorial Satisficing Bandits
Emre Ãzyıldırım, BarıŠYaycı, Umut Eren Akturk +1
We study downlink beam and rate adaptation in a multi-user mmWave MISO system where multiple base stations (BSs), each using analog beamforming from finite codebooks, serve multipl…
Contextual Combinatorial Bandits with Changing Action Sets via Gaussian Processes
Andi Nika, Sepehr Elahi, Cem Tekin
We consider a contextual bandit problem with a combinatorial action set and time-varying base arm availability. At the beginning of each round, the agent observes the set of availa…
Beyond Grids: Multi-objective Bayesian Optimization With Adaptive Discretization
Andi Nika, Sepehr Elahi, ÃaÄın Ararat +1
We consider the problem of optimizing a vector-valued objective function sampled from a Gaussian Process (GP) whose index set is a well-behaved, compact metric spa…
Federated Multi-Armed Bandits Under Byzantine Attacks
Artun Saday, Ä°lker Demirel, YiÄit Yıldırım +1
Multi-armed bandits (MAB) is a sequential decision-making model in which the learner controls the trade-off between exploration and exploitation to maximize its cumulative reward.…
Robust Pareto Set Identification with Contaminated Bandit Feedback
Ä°lter Onat Korkmaz, Efe Eren Ceyani, Kerem Bozgan +1
We consider the Pareto set identification (PSI) problem in multi-objective multi-armed bandits (MO-MAB) with contaminated reward observations. At each arm pull, with some fixed pro…