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ICML
2005
IEEE
14 years 10 months ago
Why skewing works: learning difficult Boolean functions with greedy tree learners
We analyze skewing, an approach that has been empirically observed to enable greedy decision tree learners to learn "difficult" Boolean functions, such as parity, in the...
Bernard Rosell, Lisa Hellerstein, Soumya Ray, Davi...
ISCAS
2002
IEEE
116views Hardware» more  ISCAS 2002»
14 years 2 months ago
Antisymmetries in the realization of Boolean functions
New symmetries of degree two are introduced, along with spectral techniques for identifying these symmetries. Some applications of these symmetries are discussed, in particular th...
Jacqueline E. Rice, Jon C. Muzio
SAS
1999
Springer
14 years 2 months ago
Binary Decision Graphs
Abstract. Binary Decision Graphs are an extension of Binary Decision Diagrams that can represent some infinite boolean functions. Three refinements of BDGs corresponding to class...
Laurent Mauborgne
STACS
1998
Springer
14 years 1 months ago
On Disguised Double Horn Functions and Extensions
We consider Boolean functions represented by decision lists, and study their relationships to other classes of Boolean functions. It turns out that the elementary class of 1-decis...
Thomas Eiter, Toshihide Ibaraki, Kazuhisa Makino
NIPS
2000
13 years 11 months ago
APRICODD: Approximate Policy Construction Using Decision Diagrams
We propose a method of approximate dynamic programming for Markov decision processes (MDPs) using algebraic decision diagrams (ADDs). We produce near-optimal value functions and p...
Robert St-Aubin, Jesse Hoey, Craig Boutilier