In this work we study approximation of fuzzy functions on a finite set of distinct points. Two types of approximation are considered, one method based on fuzzy linear programming p...
A novel framework for providing probabilistically-bounded approximate answers to non-holistic aggregate range queries in OLAP is presented in this paper. Such a framework allows u...
We present a general-purpose, lossless compressor for streaming data. This compressor is based on the deplump probabilistic compressor for batch data. Approximations to the infere...
Hierarchical probabilistic modeling of discrete data has emerged as a powerful tool for text analysis. Posterior inference in such models is intractable, and practitioners rely on...
Abstract. This article introduces structural aspects in an ontology of approximate reason. The basic assumption in this ontology is that approximate reason is a capability of an ag...
James F. Peters, Andrzej Skowron, Jaroslaw Stepani...