Multi-armed Bandit Framework
Cost sensitive decision tree learning using a multi armed bandit framework
... unique bandit paths in a dataset It is now simply a case of counting out the leaves, so in this problem the solution is that there are 24 potential unique bandit paths which could appear in a decision ...
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A cost sensitive decision tree learning algorithm based on a multi armed bandit framework
... the multi-armed bandit problem, in which a player in a casino has to decide which slot machine (bandit) from a selection of slot machines is likely to pay out the ...this ...
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A cost-sensitive decision tree learning algorithm based on a multi-armed bandit framework
... the multi-armed bandit problem, in which a player in a casino has to decide which slot machine (bandit) from a selection of slot machines is likely to pay out the ...this ...
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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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Transfer restless multi armed bandit policy for energy efficient heterogeneous cellular network
... Navikkumar Modi 1† , Philippe Mary 2†* and Christophe Moy 3† Abstract This paper proposes a learning policy to improve the energy efficiency (EE) of heterogeneous cellular networks. The combination of active and inactive ...
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Scalable Discrete Sampling as a Multi-Armed Bandit Problem
... MCMC framework as a transition ker- nel, we can apply immediately the theories in Mitrophanov (2005); Pillai & Smith (2014) to show that the approximate Markov chain satisfies uniform ergodicity under regular ...
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The Sample Complexity of Exploration in the Multi-Armed Bandit Problem
... The paper is organized as follows. In Section 2, we set up our framework, and since we are mainly interested in lower bounds, we restrict to the special case where each arm is a “coin,” i.e., the rewards are ...
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muMAB. A multi-armed bandit model for wireless network selection
... Acknowledgments: The research work presented in this paper was partially supported by Sapienza University of Rome, Italy within the framework of the research project “Small World routing In heterogeneous ...
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On the Complexity of Best-Arm Identification in Multi-Armed Bandit Models
... the bandit literature ...different bandit models ν and ν 0 ...different bandit models which is of interest on its own and is stated as Lemma 19 in Appendix ...exploration framework, we give in ...
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Estimation Bias in Multi-Armed Bandit Algorithms for Search Advertising
... We simulate our two stage framework for various values of T . Figures 1a and 1b show the effect of sample selection debiasing (see Section 3, 3.2) on the expected revenue where one uses adaptive learning. (the UCB ...
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Combinatorial Multi-Armed Bandit and Its Extension to Probabilistically Triggered Arms
... general framework for a large class of combinatorial multi-armed bandit (CMAB) problems, where subsets of base arms with unknown distributions form super ...
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Customer Acquisition via Display Advertising Using Multi-Armed Bandit Experiments
... during our experiment, and most of the variation in aggregate conversion rates, viewed in Fig- ure 3 can be attributed to changes in the mix of impression volume across media placements outside of our decision-making ...
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A multi-armed bandit approach for batch mode active learning on information networks
... We evaluate MABAL on three classification tasks over two real world datasets against simple heuristic and literature active learning baselines. To demon- strate that MABAL is not dependent on any particular collective ...
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Selecting Multiple Web Adverts - a Contextual Multi-armed Bandit with State Uncertainty
... Williamson (2006) has most in common with our work. Here, the advertiser must bid for search advertising slots based on search keywords with a limited budget. Their method combines a stochastic knapsack with ...
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Enhancing Evolutionary Conversion Rate Optimization via Multi-Armed Bandit Algorithms
... Challenges in Real-World Evolutionary CRO When the Evolutionary CRO methods were taken out of the laboratory and into the real world application, it became clear that there were new and interesting challenges that needed ...
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Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems
... the multi-armed bandit and the reinforcement learning ...the bandit problem we show that given n arms, it suffices to pull the arms a total of O (n/ε 2 )log(1/δ) times to find an ε-optimal arm ...
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Multi-Armed Bandit Algorithms for a Mobile Service Robot's Spare Time in a Structured Environment
... Previous works have also explored the concept of a service robot learning in its spare time. With the Dora the Explorer robot, Hanheide et al. presented a framework for generating and managing goals that the robot ...
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Lower Bounds and Selectivity of Weak-Consistent Policies in Stochastic Multi-Armed Bandit Problem
... Moreover, Theorem 8 shows that methods that would be inspired by related literature in adver- sarial bandit can not apply to our framework. As we said, this impossibility may come from the fact that we can ...
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Overlapping Multi-Bandit Best Arm Identification
... The multi-armed bandit (MAB) problem [1] provides a versatile framework for sequentially searching for high-reward actions, with applications including clinical trials [2], online advertising ...
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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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