Radial level planarity testing and embedding in linear time.
Ramsey partitions and proximity data structures
This paper addresses two problems lying at the intersection of geometric analysis and theoretical computer science: The non-linear isomorphic Dvoretzky theorem and the design of good approximate distance oracles for large distortion.We introduce the notion of Ramsey partitions of a finite metric space, and show that the existence of good Ramsey partitions implies a solution to the metric Ramsey problem for large distortion (also known as the non-linear version of the isomorphic Dvoretzky theorem,...
Random subnetworks of random sorting networks.
Range Searching with Efficient Hierarchical Cuttings.
Reasoning Methods for Designing and Surveying Relationships Described by Sets of Functional Constraints
This work is supported by the Hungarian Scientific Research Fund (OTKA), grant T042706.Current methods of database schema design are usually based on modeling the real world as entity (or object) classes with relationships among them. Properties of relationships can be described by semantical database constraints. One of them is functional dependency, which has a key role in traditional database design. The three basic types of binary relationships that can be described by functional dependencies...
Rebalancing operations for deletions in AVL-trees
Recent Advances in Stream Cipher Cryptanalysis
Relational data base design using refinement rules
Relational structures and dependence spaces
Remarks concerning RSA-cryptosystem exponents
Repetitions and permutations of columns in the semijoin algebra
Codd defined the relational algebra [E.F. Codd, Communications of the ACM 13 (1970) 377–387; E.F. Codd, Relational completeness of data base sublanguages, in Data Base Systems, R. Rustin, Ed., Prentice-Hall (1972) 65–98] as the algebra with operations projection, join, restriction, union and difference. His projection operator can drop, permute and repeat columns of a relation. This permuting and repeating of columns does not really add expressive power to the relational algebra. Indeed, using the...
Repetitions and permutations of columns in the semijoin algebra
Codd defined the relational algebra [E.F. Codd, Communications of the ACM13 (1970) 377–387; E.F. Codd, Relational completeness of data base sublanguages, in Data Base Systems, R. Rustin, Ed., Prentice-Hall (1972) 65–98] as the algebra with operations projection, join, restriction, union and difference. His projection operator can drop, permute and repeat columns of a relation. This permuting and repeating of columns does not really add expressive power to the relational algebra. Indeed, ...
Representación de datos de conjuntos aproximados mediante diagramas de decisión binarios.
A new information system representation, which inherently represents indiscernibility is presented. The basic structure of this representation is a Binary Decision Diagram. We offer testing results for converting large data sets into a Binary Decision Diagram Information System representation, and show how indiscernibility can be efficiently determined. Furthermore, a Binary Decision Diagram is used in place of a relative discernibility matrix to allow for more efficient determination of the discernibility...
Retrieving library functions by unifying types modulo linear isomorphism
Reversal distance for strings with duplicates: linear time approximation using hitting set.
Rough membership functions: a tool for reasoning with uncertainty
A variety of numerical approaches for reasoning with uncertainty have been investigated in the literature. We propose rough membership functions, rm-functions for short, as a basis for such reasoning. These functions have values in the interval [0,1] and are computable on the basis of the observable information about the objects rather than on the objects themselves. We investigate properties of the rm-functions. In particular, we show that our approach is intensional with respect to the class of...
Rough modeling - a bottom-up approach to model construction
Traditional data mining methods based on rough set theory focus on extracting models which are good at classifying unseen obj-ects. If one wants to uncover new knowledge from the data, the model must have a high descriptive quality-it must describe the data set in a clear and concise manner, without sacrificing classification performance. Rough modeling, introduced by Kowalczyk (1998), is an approach which aims at providing models with good predictive emphand descriptive qualities, in addition to...