Multi-armed bandit
Algorithms for the multi-armed bandit problem
... stochastic multi-armed bandit problem is an important model for studying the exploration- exploitation tradeoff in reinforcement ...popular multi-armed bandit ...of bandit ...
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Monotone multi-armed bandit allocations
... Peter Auer, Nicol` o Cesa-Bianchi, Yoav Freund, and Robert E. Schapire. The nonstochastic multi- armed bandit problem. SIAM J. Comput., 32(1):48–77, 2002b. Preliminary version in 36th IEEE FOCS, ...
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Multi-armed Bandit Problems with History
... stochastic multi-armed bandit ...stochastic bandit settings, such as bandits with a con- tinuum of arms, dueling bandits, ...for bandit problems with historic ...
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Mechanisms with learning for stochastic multi armed bandit problems
... The multi-armed bandit (MAB) problem is a widely studied problem in machine learning litera- ture in the context of online learning. In this article, our focus is on a specific class of problems ...
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Optimizing Adaptive Marketing Experiments with the Multi-Armed Bandit
... the Multi-Armed Bandit Abstract Sequential decision making is central to a range of marketing ...the multi-armed bandit, the conceptual and methodological backbone of this ...
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The Sample Complexity of Exploration in the Multi-Armed Bandit Problem
... Lower bounds for different variants of the multi-armed bandit have been studied by several authors. For the expected regret model, where the regret is defined as the difference between the ideal ...
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The Non-stationary Stochastic Multi-armed Bandit Problem
... the multi-armed bandit problem that generalize the stationary stochastic, piecewise- stationary and adversarial bandit ...switching bandit problem with SER4 by adding a probability of ...
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Towards an Improved Strategy for Solving Multi Armed Bandit Problem
... Abstract: Multi-Armed Bandit (MAB) problem is one of the classical reinforcements learning problems that describe the friction between the agent’s exploration and ...
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A multi-armed bandit approach for exploring partially observed networks
... a multi-armed bandit based exploration algorithm for par- tially observed incomplete ...nonparametric multi-armed bandit algorithm iKNN-UCB with sublinear ...iKNN-UCB ...
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muMAB. A multi-armed bandit model for wireless network selection
... In this work, a new model for Multi-Armed Bandit problems, referred to as muMAB, was proposed. The model introduces the presence of two different actions: to measure and to use. In addition, the ...
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On the Complexity of Best-Arm Identification in Multi-Armed Bandit Models
... stochastic multi-armed bandit model is a simple abstraction that has proven useful in many different contexts in statistics and machine ...two armed-bandits, we derive refined lower bounds in ...
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Estimation Bias in Multi-Armed Bandit Algorithms for Search Advertising
... In search advertising, the search engine needs to select the most profitable adver- tisements to display, which can be formulated as an instance of online learning with partial feedback, also known as the stochastic ...
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Multi-Armed Bandit in Action: Optimizing Performance in Dynamic Hybrid Networks
... Multi-Armed Bandit in Action: Optimizing Performance in Dynamic Hybrid Networks Sébastien Henri , Christina Vlachou , and Patrick Thiran, Fellow, IEEE Abstract— Today’s home networks are often ...
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A Multi-Armed Bandit Model Selection for Cold-Start User Recommendation
... philippe.preux@inria.fr ABSTRACT How can we effectively recommend items to a user about whom we have no information? This is the problem we focus on in this paper, known as the cold-start problem. In most existing works, ...
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Slow Fading Channel Selection: A Restless Multi-Armed Bandit Formulation
... I. I NTRODUCTION Next generation of wireless networks is expected to be characterized by a high decentralization/distribution of control functions among nodes to support self-organizing and self- healing capabilities. ...
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Combinatorial Multi-Armed Bandit and Its Extension to Probabilistically Triggered Arms
... We define a general framework for a large class of combinatorial multi-armed bandit (CMAB) problems, where subsets of base arms with unknown distributions form super arms. In each round, a super arm ...
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Cooperation control in Parallel SAT Solving: a Multi-armed Bandit Approach
... Abstract: In recent years, Parallel SAT solvers have leveraged with the so called Parallel Portfolio architecture. In this setting, a collection of independent Conflict- Directed Clause Learning (CDCL) algorithms compete ...
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Partially Observable Multi-Sensor Sequential Change Detection: A Combinatorial Multi-Armed Bandit Approach
... Observable Multi-sensor Sequential Change Detec- tion (POMSCD), where only a subset of sensors can be ob- served to monitor a target system for change-point detection at each online learning ...traditional ...
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Customer Acquisition via Display Advertising Using Multi-Armed Bandit Experiments
... percentage of impressions to allocate to each ad? This paper answers that question, resolving the well-known “learn-and-earn” trade-off using multi-armed bandit (MAB) methods. The online advertiser’s ...
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Training a Quantum Neural Network to Solve the Contextual Multi Armed Bandit Problem
... contextual multi-armed bandit problem, a problem in the domain of reinforcement learn- ing, which demonstrates that quantum reinforcement learning algorithms can be learned by a quantum ...
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