— The applicability of complex networks of spiking neurons as a general purpose machine learning technique remains open. Building on previous work using macroscopic exploration o...
Abstract. The regularization functional induced by the graph Laplacian of a random neighborhood graph based on the data is adaptive in two ways. First it adapts to an underlying ma...
We design algorithms for two online variance minimization problems. Specifically, in every trial t our algorithms get a covariance matrix Ct and try to select a parameter vector wt...
Basically, instrumental conditioning is learning through consequences: Behavior that produces positive results (high “instrumental response”) is reinforced, and that which pro...
Hierarchical reinforcement learning is a general framework which attempts to accelerate policy learning in large domains. On the other hand, policy gradient reinforcement learning...