There has been a recent and increasing interest in computer analysis and recognition of human motion. Previously we presented an efficient real-time approach for representing huma...
This paper describes a method for hierarchical reinforcement learning in which high-level policies automatically discover subgoals, and low-level policies learn to specialize for ...
Using an adequate representation is often the key to solve complex problems in Artificial Intelligence. Hierarchical shape representations are very convenient in domains -such as ...
: In agglomerative hierarchical clustering, pair-group methods suffer from a problem of non-uniqueness when two or more distances between different clusters coincide during the ama...
We propose a novel hierarchical clustering algorithm for data-sets in which only pairwise distances between the points are provided. The classical Hungarian method is an efficient...