This paper studies the “explanation problem” for tree- and linearly-ordered array data, a problem motivated by database applications and recently solved for the one-dimensiona...
Howard J. Karloff, Flip Korn, Konstantin Makaryche...
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
We address the problem of efficiently gathering correlated data from a wireless sensor network, with the aim of designing algorithms with provable optimality guarantees, and unders...
Matrix decomposition methods provide representations of an object-variable data matrix by a product of two different matrices, one describing relationship between objects and hidd...
We present a problem of factor analysis of three-way binary data, i.e. data described by a 3-dimensional binary matrix I, describing a relationship between objects, attributes, an...