In this paper we propose a novel parameterized macromodeling technique for analog circuits. Unlike traditional macromodels that are only extracted for a small variation space, our...
We consider the problem of learning to map between two vector spaces given pairs of matching vectors, one from each space. This problem naturally arises in numerous vision problem...
We introduce a new type of Self-Organizing Map (SOM) to navigate in the Semantic Space of large text collections. We propose a "hyperbolic SOM" (HSOM) based on a regular...
Recent research has demonstrated that useful POMDP solutions do not require consideration of the entire belief space. We extend this idea with the notion of temporal abstraction. ...
The work of Boden on the nature of creativity has been extremely influential, particularly the hypothesis that the highest form of creativity results from transformation of a conce...