This paper presents an algorithm for extract ing propositions from trained neural networks. The algorithm is a decompositional approach which can be applied to any neural networ...
We present a model that enables us to analyze the running time of an algorithm on a computer with a memory hierarchy with limited associativity, in terms of various cache parameter...
Guided by an initial idea of building a complex (non linear) decision surface with maximal local margin in input space, we give a possible geometrical intuition as to why K-Neares...
This paper presents a connected coherence tree algorithm (CCTA) for image segmentation with no prior knowledge. It aims to find regions of semantic coherence based on the proposed ...
Many recent successful planners use domain-independent heuristics to speed up the search for a valid plan. An orthogonal approach to accelerating search is to identify and remove r...