Update games and update networks

Extracting Winning Strategies in Update Games

This paper investigates algorithms for extracting winning strategies in two-player games played on finite graphs. We focus on a special class of games called update games. We present a procedure for extracting winning strategies in update games by constructing strategies explicitly. This is based on an algorithm that solves update games in quadratic time. We also show that solving update games ...

Pathogenesis and Causes of Premature Ovarian Failure:An Update

A Multiagent Reinforcement Learning algorithm to solve the Community Detection Problem

Community detection is a challenging optimization problem that consists of searching for communities that belong to a network under the assumption that the nodes of the same community share properties that enable the detection of new characteristics or functional relationships in the network. Although there are many algorithms developed for community detection, most of them are unsuitable when ...

Gradient conjugate priors and deep neural networks

The paper deals with learning the probability distribution of the observed data by artificial neural networks. We suggest a so-called gradient conjugate prior (GCP) update appropriate for neural networks, which is a modification of the classical Bayesian update for conjugate priors. We establish a connection between the gradient conjugate prior update and the maximization of the log-likelihood ...

O21: Update and Future Directions in Poststroke Epilepsy

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