We develop a framework for the image segmentation problem based on a new graph-theoretic formulation of clustering. The approach is motivated by the analogies between the intuitiv...
Abstract. Application and development of specialized machine learning techniques is gaining increasing attention in the intrusion detection community. A variety of learning techniq...
Delta compression techniques are commonly used to succinctly represent an updated version of a file with respect to an earlier one. In this paper, we study the use of delta compr...
Zan Ouyang, Nasir D. Memon, Torsten Suel, Dimitre ...
We propose in this paper a general framework for integrating inductive and case-based reasoning (CBR) techniques for diagnosis tasks. We present a set of practical integrated appro...
Eric Auriol, Michel Manago, Klaus-Dieter Althoff, ...
Subspace clustering and feature extraction are two of the most commonly used unsupervised learning techniques in computer vision and pattern recognition. State-of-theart technique...
Risheng Liu, Zhouchen Lin, Fernando De la Torre, Z...