To address these problems, we propose an algorithm named Dynamic Clustering based Contextual Combinatorial Multi-Armed Bandits (DC3MAB), which consists of three configurable key components. Specifically, a dyna
Dynamic clustering based contextual combinatorial multi-armed bandit for online recommendation 2022, Knowledge Based Systems Citation Excerpt : Therefore, we will study various types of implicit feedback, classify them, observe their impact on the model, and design a multi-class reward mechanism based ...
Bandit-based Large-Neighborhood Search To solve combinatorial optimization problems, MABWiser is integrated intoAdaptive Large Neighborhood Search. The ALNS library enables building metaheuristics for complex optimization problems, whereby MABWiser helps selecting the next best destroy, repair operation (arm)...
We formulate the problem as a novel variant of a contextual combinatorial multi-armed bandit problem. The context takes the form of a probability distribution over the user's latent topic preference, and rewards are a particular nonlinear function of the selected set and the context. These ...
To address this issue, we consider a combinatorial bandit problem where the learner selects S actions from a base set of K actions, and displays the results in S (out of M) different positions. The aim is to maximize the cumulative reward or equivalently minimize the regret with respect to...
Thus, it is crucial to select the optimal portfolio of resources from the entire set of resources, which falls under the realm of combinatorial optimization, and can be formulated as a mixed-integer linear programming (MILP) problem [5]. Although such a MILP problem can be solved by the ...
Thus, it is crucial to select the optimal portfolio of resources from the entire set of resources, which falls under the realm of combinatorial optimization, and can be formulated as a mixed-integer linear programming (MILP) problem [5]. Although such a MILP problem can be solved by the ...
Thus, it is crucial to select the optimal portfolio of resources from the entire set of resources, which falls under the realm of combinatorial optimization, and can be formulated as a mixed-integer linear programming (MILP) problem [5]. Although such a MILP problem can be solved by the ...
Thus, it is crucial to select the optimal portfolio of resources from the entire set of resources, which falls under the realm of combinatorial optimization, and can be formulated as a mixed-integer linear programming (MILP) problem [5]. Although such a MILP problem can be solved by the ...