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263
Auditing Boolean Attributes
 Journal of Computer and System Sciences
, 2000
"... We study the problem of auditing databases which support statistical sum queries to protect the security of sensitive information; we focus on the special case in which the sensitive information is Boolean. Principles and techniques developed for the security of statistical databases in the case ..."
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Cited by 66 (0 self)
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that the problem is NPhard even in the twodimensional case). The second is an approximate algorithm that maintains security, although it may be too restrictive. Finally, we consider a "dual" variant, with continuous data but an aggregate function that is combinatorial in nature. Specifically, we
Sparse Boolean equations and circuit lattices
"... Abstract. A system of Boolean equations is called sparse if each equation depends on a small number of variables. Finding efficiently solutions to the system is an underlying hard problem in the cryptanalysis of modern ciphers. In this paper we study new properties of the Agreeing Algorithm, which w ..."
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Cited by 1 (1 self)
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Abstract. A system of Boolean equations is called sparse if each equation depends on a small number of variables. Finding efficiently solutions to the system is an underlying hard problem in the cryptanalysis of modern ciphers. In this paper we study new properties of the Agreeing Algorithm, which
Recognition of Interval Boolean Functions
, 2006
"... Interval functions constitute quite a special class of Boolean functions for which it is very easy and fast to determine their functional value on a specified input vector. Their value is true if and only if the input data viewed as an nbit number belongs to the interval [a, b] corresponding to the ..."
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to the function concerned. Therefore we study the problem of deciding whether given DNF represents interval function and if so then we also want to output the corresponding interval. For general Boolean functions this is coNPhard. In our article we present a polynomial algorithm which works for monotone
DomainIndependent Extensions to GSAT: Solving Large Structured Satisfiability Problems
 PROC. IJCAI93
, 1993
"... GSAT is a randomized local search procedure for solving propositional satisfiability problems (Selman et al. 1992). GSAT can solve hard, randomly generated problems that are an order of magnitude larger than those that can be handled by more traditional approaches such as the DavisPutnam proc ..."
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Cited by 227 (10 self)
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Putnam procedure. GSAT also efficiently solves encodings of graph coloring problems, Nqueens, and Boolean induction. However, GSAT does not perform as well on handcrafted encodings of blocksworld planning problems and formulas with a high degree of asymmetry. We present three strategies that dramatically
Boolean Analysis of Incomplete Examples
 RUTCOR RESEARCH REPORT, RRR 796, RUTCOR  RUTGERS UNIVERSITY'S CENTER FOR OPERATIONS RESEARCH
, 1996
"... As a form of knowledge acquisition from data, we consider the problem of deciding whether there exists an extension of a partially defined Boolean function with missing data ( T , F ), where T (resp., F ) is a set of positive (resp., negative) examples. Here, "#" denotes a missing ..."
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Cited by 3 (3 self)
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As a form of knowledge acquisition from data, we consider the problem of deciding whether there exists an extension of a partially defined Boolean function with missing data ( T , F ), where T (resp., F ) is a set of positive (resp., negative) examples. Here, "#" denotes a missing
On Constrained Boolean Pareto Optimization
"... Pareto optimization solves a constrained optimization task by reformulating the task as a biobjective problem. Pareto optimization has been shown quite effective in applications; however, it has little theoretical support. This work theoretically compares Pareto optimization with a penalty approach ..."
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Cited by 1 (1 self)
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approach, which is a common method transforming a constrained optimization into an unconstrained optimization. We prove that on two large classes of constrained Boolean optimization problems, minimum matroid optimization (Psolvable) and minimum cost coverage (NPhard), Pareto optimization is more
BOOM  a Boolean Minimizer
, 2001
"... This report presents an algorithm for twolevel Boolean minimization (BOOM) based on a new implicant generation paradigm. In contrast to all previous minimization methods, where the implicants are generated bottomup, the proposed approach uses a topdown approach. Thus instead of increasing the dim ..."
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Cited by 1 (1 self)
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. The proposed minimization method is efficient above all for functions with several hundreds of input variables and with a large portion of don't care states. The minimization method has been tested on several different kinds of problems. The MCNC standard benchmarks were solved several times in order
Extensions of Partially Defined Boolean Functions with Missing Data
 RUTCOR RESEARCH REPORT 696, RUTGERS UNIVERSITY, 640 BARTHOLOMEW ROAD, PISCATAWAY, NJ
, 1996
"... As a form of knowledge acquisition from data, we consider the problem which, given a partially defined Boolean function with missing data (pBmd) ( ~ T ; ~ F ), where ~ T ` f0; 1; g n and ~ F ` f0; 1; g n , respectively, represent "positive examples" and "negative examples" ..."
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Cited by 11 (7 self)
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As a form of knowledge acquisition from data, we consider the problem which, given a partially defined Boolean function with missing data (pBmd) ( ~ T ; ~ F ), where ~ T ` f0; 1; g n and ~ F ` f0; 1; g n , respectively, represent "positive examples" and "negative examples
On the analysis of a simple evolutionary algorithm on quadratic pseudoboolean functions
, 2002
"... Evolutionary algorithms are randomized search heuristics, which are often used as function optimizers. In this paper the wellknown (1+1) Evolutionary Algorithm ((1+1) EA) and its multistart variants are studied. Several results on the expected runtime of the (1+1) EA on linear or unimodal functions ..."
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Cited by 24 (11 self)
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functions have already been presented by other authors. This paper is focused on quadratic pseudoboolean functions, i. e., polynomials of degree 2, a class of functions containing NPhard optimization problems. Subclasses of the class of all quadratic functions are identified where the (1+1) EA
Boolean Operations on PointSampled Geometry
, 2005
"... In computer graphics boolean operations have been around for years. In contrast, point sampled geometry models represent a new and stirring side of graphics which is researched mostly in the last couple of years. Papers about the combination of CSG and surfels only appeared recently, and itâ€™s hard t ..."
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and analyze efficiency. Finally, we propose a new algorithm for speeding up the update of space partitioning data structure needed for real time CSG operation.
Results 1  10
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263