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AAAI
1993
13 years 9 months ago
Reasoning With Characteristic Models
Formal AI systems traditionally represent knowledge using logical formulas. We will show, however, that for certain kinds of information, a modelbased representation is more compa...
Henry A. Kautz, Michael J. Kearns, Bart Selman
AAAI
1996
13 years 9 months ago
A Connectionist Framework for Reasoning: Reasoning with Examples
We present a connectionist architecture that supports almost instantaneous deductive and abductive reasoning. The deduction algorithm responds in few steps for single rule queries...
Dan Roth
NIPS
1996
13 years 9 months ago
Combinations of Weak Classifiers
To obtain classification systems with both good generalizat`ion performance and efficiency in space and time, we propose a learning method based on combinations of weak classifiers...
Chuanyi Ji, Sheng Ma
SODA
1996
ACM
95views Algorithms» more  SODA 1996»
13 years 9 months ago
RNC Algorithms for the Uniform Generation of Combinatorial Structures
We describe several RNC algorithms for generating graphs and subgraphs uniformly at random. For example, unlabelled undirected graphs are generated in O(lg3 n) time using O n2 lg3...
Michele Zito, Ida Pu, Martyn Amos, Alan Gibbons
AAIP
2009
13 years 8 months ago
Incremental Learning in Inductive Programming
Inductive programming systems characteristically exhibit an exponential explosion in search time as one increases the size of the programs to be generated. As a way of overcoming ...
Robert Henderson