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» Lattice-based computation of Boolean functions
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MFCS
2004
Springer
13 years 10 months ago
Approximating Boolean Functions by OBDDs
In learning theory and genetic programming, OBDDs are used to represent approximations of Boolean functions. This motivates the investigation of the OBDD complexity of approximatin...
Andre Gronemeier
CPAIOR
2007
Springer
13 years 11 months ago
On Boolean Functions Encodable as a Single Linear Pseudo-Boolean Constraint
A linear pseudo-Boolean constraint (LPB) is an expression of the form a1 · 1 + . . . + am · m ≥ d, where each i is a literal (it assumes the value 1 or 0 depending on whether a...
Jan-Georg Smaus
AMC
2006
125views more  AMC 2006»
13 years 4 months ago
A symbolic and algebraic computation based Lambda-Boolean reduction machine via PROLOG
This paper presents a new Lambda-Boolean reduction machine for Lambda-Boolean and Lambda-Beta Boolean reductions in the context of Lambda Calculus and introduces the role of Churc...
Seref Mirasyedioglu, Tolga Güyer
CEC
2005
IEEE
13 years 10 months ago
XCS with computed prediction for the learning of Boolean functions
Computed prediction represents a major shift in learning classifier system research. XCS with computed prediction, based on linear approximators, has been applied so far to functi...
Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wils...
COCO
1991
Springer
112views Algorithms» more  COCO 1991»
13 years 8 months ago
Randomized vs.Deterministic Decision Tree Complexity for Read-Once Boolean Functions
We consider the deterministic and the randomized decision tree complexities for Boolean functions, denoted DC(f) and RC(f), respectively. A major open problem is how small RC(f) ca...
Rafi Heiman, Avi Wigderson