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» On Learning Boolean Functions
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ECCC
2010
124views more  ECCC 2010»
13 years 10 months ago
Lower Bounds and Hardness Amplification for Learning Shallow Monotone Formulas
Much work has been done on learning various classes of "simple" monotone functions under the uniform distribution. In this paper we give the first unconditional lower bo...
Vitaly Feldman, Homin K. Lee, Rocco A. Servedio
EC
2006
121views ECommerce» more  EC 2006»
13 years 10 months ago
A Study of Structural and Parametric Learning in XCS
The performance of a learning classifier system is due to its two main components. First, it evolves new structures by generating new rules in a genetic process; second, it adjust...
Tim Kovacs, Manfred Kerber
BMCBI
2010
233views more  BMCBI 2010»
13 years 10 months ago
Odefy -- From discrete to continuous models
Background: Phenomenological information about regulatory interactions is frequently available and can be readily converted to Boolean models. Fully quantitative models, on the ot...
Jan Krumsiek, Sebastian Pölsterl, Dominik M. ...
JSAT
2006
134views more  JSAT 2006»
13 years 10 months ago
Pueblo: A Hybrid Pseudo-Boolean SAT Solver
This paper introduces a new hybrid method for efficiently integrating Pseudo-Boolean (PB) constraints into generic SAT solvers in order to solve PB satisfiability and optimization...
Hossein M. Sheini, Karem A. Sakallah
CCS
2006
ACM
14 years 1 months ago
Cryptanalysis of the "Grain" family of stream ciphers
Let us have an NLFSR with the feedback function g(x) and an LFSR with the generating polynomial f(x). The function g(x) is a Boolean function on the state of the NLFSR and the LFS...
Alexander Maximov