Hierarchical clustering is used widely to organize data and search for patterns. Previous algorithms assume that the body of data being clustered is fixed while the algorithm runs...
H. Van Dyke Parunak, Richard Rohwer, Theodore C. B...
Hierarchical reinforcement learning has been proposed as a solution to the problem of scaling up reinforcement learning. The RLTOPs Hierarchical Reinforcement Learning System is an...
Hierarchical penalization is a generic framework for incorporating prior information in the fitting of statistical models, when the explicative variables are organized in a hiera...
Marie Szafranski, Yves Grandvalet, Pierre Morizet-...
We introduce the Hierarchically Growing Hyperbolic Self-Organizing Map (H2 SOM) featuring two extensions of the HSOM (hyperbolic SOM): (i) a hierarchically growing variant that al...
We present a novel approach to natural language generation (NLG) that applies hierarchical reinforcement learning to text generation in the wayfinding domain. Our approach aims to...