Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 11 of 11 for “"Bandit algorithms"”.
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Multi-armed bandits and applications to large datasets
This thesis considers the multi-armed bandit (MAB) problem, both the traditional bandit feedback and graphical bandits when there is side information. Motivated by the Boltzmann exploration algorithm often used in the more general context of reinforcement learning, we present Almost Boltzmann …
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Power Control and Resource Allocation for QoS-Constrained Wireless Networks
… power control, matching theory and multi-armed bandit algorithms are employed in our investigations. In this dissertation, we first consider a cluster-based cooperative wireless network utilizing a centralized cooperation model. The dynamic power control and optimization problem is analyzed in …
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Learning Heterogeneous Resource-Constrained Task Allocation Using Concurrent Multi-Task Bandits
… algorithm called Concurrent Multi-Task Adaptive Bandits (CMTAB), which leverages and builds upon continuum-armed bandit algorithms. Our experiments, which involve detailed numerical simulations and a simulated emergency response task, demonstrate that CMTAB is effective at balancing exploration …
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The Modeling Spectrum of Data-Driven Decision Making
… practices in the framework of multi-armed bandits with expert advice. We extend the setting from finitely many experts to any countably infinite set and provide algorithms that are provably optimal. Second, we explore optimizing perturbations for cell reprogramming in batched experiments. …
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New Spatio-temporal Hawkes Process Models For Social Good
… integrate Hawkes Process models with multi-armed bandit algorithms, high dimensional marks, and high-dimensional auxiliary data to solve problems in search and rescue, forecasting infectious disease, and early detection of overdose spikes. In Chapter 3, we develop a method applications to the …
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ONLINE LEARNING WITH BANDITS FOR COVERAGE
… learning algorithm inspired by the Multi-Armed Bandit problem to solve the online recommendation system problem. We introduce a graph-based mechanism to improve the user coverage by recommended items and show that the mechanism can facilitate the coordination between bandits and therefore, …
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Sequential decision making with feature-linear models
… as linear in some feature space. We consider a bandit problem, where the rewards are linear in a reproducing kernel Hilbert space, and a reinforcement learning setting with features given by a neural network. The thesis is split into two parts accordingly. In part I, we introduce a new algorithm …
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Regulating exploration in multi-armed bandit problems with time patterns and dying arms
… holidays. The standard paradigm of multi-armed bandit analysis does not take these known patterns into account. This means that for applications in retail, where prices are fixed for periods of time, current bandit algorithms will not suffice. This work provides a framework and methods that take …
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Bandits in autoregressive Markov models
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2026-08-01
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New Directions in Bandit Learning: Singularities and Random Walk Feedback
<p>My thesis focuses new directions in bandit learning problems. In Chapter 1, I give an overview of the bandit learning literature, which lays the discussion framework for studies in Chapters 2 and 3. In Chapter 2, I study bandit learning problem in metric measure spaces. I start with multi-armed …
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Online advertisements and multi-armed bandits
We investigate a number of multi-armed bandit problems that model different aspects of online advertising, beginning with a survey of the key techniques that are commonly used to demonstrate the theoretical limitations and achievable results for the performance of multi-armed bandit algorithms. We …