This work takes place in the context of hierarchical stochastic models for the resolution of discrete inverse problems from low level vision. Some of these models lie on the nodes...
Hierarchical reinforcement learning is a general framework which attempts to accelerate policy learning in large domains. On the other hand, policy gradient reinforcement learning...
Originally, the hierarchical coding structure was proposed to achieve temporal scalability. Soon after, it was realized that with a proper quantization parameter cascading (QPC) s...
Background: To infer the tree of life requires knowledge of the common characteristics of each species descended from a common ancestor as the measuring criteria and a method to c...
Sok June Oh, Je-Gun Joung, Jeong Ho Chang, Byoung-...