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FOCS
1990
IEEE
15 years 4 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
JAIR
2010
111views more  JAIR 2010»
14 years 10 months ago
Grounding FO and FO(ID) with Bounds
Grounding is the task of reducing a first-order theory and finite domain to an equivalent propositional theory. It is used as preprocessing phase in many logic-based reasoning s...
Johan Wittocx, Maarten Mariën, Marc Denecker
AAAI
2006
15 years 1 months ago
The Impact of Balancing on Problem Hardness in a Highly Structured Domain
Random problem distributions have played a key role in the study and design of algorithms for constraint satisfaction and Boolean satisfiability, as well as in our understanding o...
Carlos Ansótegui, Ramón Béjar...
ACMSE
2010
ACM
14 years 10 months ago
Automatic generation of model traversals from metamodel definitions
Developing software from models is a growing practice and there exist many model-based tools (e.g., model editors, model interpreters) for supporting model-driven engineering. Eve...
Tomaz Lukman, Marjan Mernik, Zekai Demirezen, Barr...
AMAI
2002
Springer
14 years 11 months ago
A Complete Axiomatization for Blocks World
Blocks World (BW) has been one of the most popular model domains in AI history. However, there has not been serious work on axiomatizing the state constraints of BW and giving jus...
Stephen A. Cook, Yongmei Liu