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FOCS
1990
IEEE
15 years 10 months ago
Separating Distribution-Free and Mistake-Bound Learning Models over the Boolean Domain
Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
Avrim Blum
BMCBI
2006
137views more  BMCBI 2006»
15 years 6 months ago
A classification-based framework for predicting and analyzing gene regulatory response
Background: We have recently introduced a predictive framework for studying gene transcriptional regulation in simpler organisms using a novel supervised learning algorithm called...
Anshul Kundaje, Manuel Middendorf, Mihir Shah, Chr...
CORR
2004
Springer
177views Education» more  CORR 2004»
15 years 6 months ago
Typestate Checking and Regular Graph Constraints
We introduce regular graph constraints and explore their decidability properties. The motivation for regular graph constraints is 1) type checking of changing types of objects in ...
Viktor Kuncak, Martin C. Rinard
DATAMINE
1999
143views more  DATAMINE 1999»
15 years 6 months ago
Partitioning Nominal Attributes in Decision Trees
To find the optimal branching of a nominal attribute at a node in an L-ary decision tree, one is often forced to search over all possible L-ary partitions for the one that yields t...
Don Coppersmith, Se June Hong, Jonathan R. M. Hosk...
TIT
2002
95views more  TIT 2002»
15 years 6 months ago
On sequential strategies for loss functions with memory
The problem of optimal sequential decision for individual sequences, relative to a class of competing o -line reference strategies, is studied for general loss functions with memo...
Neri Merhav, Erik Ordentlich, Gadiel Seroussi, Mar...