Advisors
Now showing items 1-11 of 11
-
Adaptive ambulance redeployment via multi-armed bandits
(Bilkent University, 2019-09)Emergency Medical Services (EMS) provide the necessary resources when there is a need for immediate medical attention and play a signi cant role in saving lives in the case of a life-threatening event. Therefore, it is ... -
Algorithms and regret bounds for multi-objective contextual bandits with similarity information
(Bilkent University, 2019-01)Contextual bandit algorithms have been shown to be e ective in solving sequential decision making problems under uncertain environments, ranging from cognitive radio networks to recommender systems to medical diagnosis. ... -
Contextual combinatorial volatile multi-armed bandits in compact context spaces
(Bilkent University, 2021-07)We consider the contextual combinatorial volatile multi-armed bandit (CCV-MAB) problem in compact context spaces, simultaneously taking into consideration all of its individual features, thus providing a general framework ... -
Contextual multi-armed bandits with structured payoffs
(Bilkent University, 2020-09)Multi-Armed Bandit (MAB) problems model sequential decision making under uncertainty. In traditional MAB, the learner selects an arm in each round, and then, observes a random reward from the arm’s unknown reward ... -
Diabetes management VIA gaussian process bandits
(Bilkent University, 2021-10)Management of chronic diseases such as diabetes mellitus requires adaptation of treatment regimes based on patient characteristics and response. There is no single treatment that fits all patients in all contexts; moreover, ... -
Fully distributed bandit algorithm for the joint channel and rate selection problem in heterogeneous cognitive radio networks
(Bilkent University, 2020-12)We consider the problem of the distributed sequential channel and rate selection in cognitive radio networks where multiple users choose channels from the same set of available wireless channels and pick modulation and ... -
Multi-armed bandit algorithms for communication networks and healthcare
(Bilkent University, 2022-06)Multi-armed bandits (MAB) is a well-established sequential decision-making framework. While the simplest MAB framework is useful in modeling a wide range of real-world applications ranging from adaptive clinical trial ... -
Online learning in structured Markov decision processes
(Bilkent University, 2017-07)This thesis proposes three new multi-armed bandit problems, in which the learner proceeds in a sequence of rounds where each round is a Markov Decision Process (MDP). The learner's goal is to maximize its cumulative ... -
Personalizing treatments via contextual multi-armed bandits by identifying relevance
(Bilkent University, 2019-08)Personalized medicine offers specialized treatment options for individuals which is vital as every patient is different. One-size-fits-all approaches are often not effective and most patients require personalized care ... -
Prediction with expert advice: on the role of contexts, bandit feedback and risk-awareness
(Bilkent University, 2018-12)Along with the rapid growth in the size of data generated and collected over time, the need for developing online algorithms that can provide answers without any offline training has considerably increased. In this thesis, ... -
Robust optimization of multi-objective multi-armed bandits with contaminated bandit feedback
(Bilkent University, 2022-06)Multi-objective multi-armed bandits (MO-MAB) is an important extension of the standard MAB problem that has found a wide variety of applications ranging from clinical trials to online recommender systems. We consider Pareto ...
