A fundamental task of data analysis is comprehending what distinguishes clusters found within the data. We present the problem of mining distinguishing sets which seeks to find s...
We examine four approaches for dealing with the logical omniscience problem and their potential applicability: the syntactic approach, awareness, algorithmic knowledge, and imposs...
Based on rank-1 update, Sparse Bayesian Learning Algorithm (SBLA) is proposed. SBLA has the advantages of low complexity and high sparseness, being very suitable for large scale pr...
The reconstruction of a shape or surface from a finite set of points is a practically significant and theoretically challenging problem. This paper presents a unified view of algor...
Abstract. The problem of reconstructing a discrete set from its horizontal and vertical projections (RSP) is of primary importance in many different problems for example pattern re...