2023/07/17 · MDPs introduce two benefits: they take into account the long-term effects of each recommendation, and they take into account the expected value ...

Recommender systems — systems that suggest to users in e-commerce sites items that might interest them — adopt a static view of the recommendation process ...

MDPs introduce two benefits: they take into account the long-term effects of each recommendation, and they take into account the expected value of each ...

MDPs introduce two benefits: they take into account the long-term effects of each recommendation, and they take into account the expected value of each ...

Recommender systems — systems that suggest to users in e-commerce sites items that might interest them — adopt a static view of the recommendation process ...

Fingerprint. Dive into the research topics of 'Recommendation as a Stochastic Sequential Decision Problem'. Together they form a unique fingerprint.

In this article, a general problem of sequential statistical inference for general discrete-time stochastic processes is considered. The problem is to minimize ...

Taking this idea one step farther, we suggest that recom- mending is not simply a sequential prediction problem, but rather, a sequential decision problem. At ...

Sequential Decision Problem Modeling Library @ Castle Lab, Princeton Univ. Installation Requires Python 3 and the following packages.

Reinforcement Learning and Stochastic Optimization offers a single canonical framework that can model any sequential decision problem using five core components ...