Sciweavers

4255 search results - page 14 / 851
» On Learning Boolean Functions
Sort
View
FOCS
1989
IEEE
13 years 11 months ago
Constant Depth Circuits, Fourier Transform, and Learnability
In this paper, Boolean functions in ,4C0 are studied using harmonic analysis on the cube. The main result is that an ACO Boolean function has almost all of its “power spectrum”...
Nathan Linial, Yishay Mansour, Noam Nisan
EJC
2010
13 years 7 months ago
Minors of Boolean functions with respect to clique functions and hypergraph homomorphisms
Each clone C on a fixed base set A determines a quasiorder on the set of all operations on A by the following rule: f is a C-minor of g if f can be obtained by substituting operati...
Erkko Lehtonen, Jaroslav Nesetril
TCAD
1998
161views more  TCAD 1998»
13 years 7 months ago
Ordered Kronecker functional decision diagrams-a data structure for representation and manipulation of Boolean functions
— Ordered Kronecker functional decision diagrams (OKFDD’s) are a data structure for efficient representation and manipulation of Boolean functions. OKFDD’s are a generalizat...
Rolf Drechsler, Bernd Becker
NIPS
1994
13 years 9 months ago
Learning Stochastic Perceptrons Under k-Blocking Distributions
We present a statistical method that PAC learns the class of stochastic perceptrons with arbitrary monotonic activation function and weights wi {-1, 0, +1} when the probability d...
Mario Marchand, Saeed Hadjifaradji
ECCC
2006
96views more  ECCC 2006»
13 years 7 months ago
When Does Greedy Learning of Relevant Features Succeed? --- A Fourier-based Characterization ---
Detecting the relevant attributes of an unknown target concept is an important and well studied problem in algorithmic learning. Simple greedy strategies have been proposed that s...
Jan Arpe, Rüdiger Reischuk