Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
Pascal Poupart, Nikos A. Vlassis, Jesse Hoey, Kevi...
We consider a variant of the classic multi-armed bandit problem (MAB), which we call FEEDBACK MAB, where the reward obtained by playing each of n independent arms varies according...
Abstract. Multidimensional databases are large collections of data, often historical, used for sophisticated analysis oriented to decision making. This activity is supported by an ...
In this paper we have introduced a methodology to rank the available products in the Internet market. These rankings are based on the customers’ own preferences and also on the ...
The field of transfer learning aims to speed up learning across multiple related tasks by transferring knowledge between source and target tasks. Past work has shown that when th...