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IJCAI
1993
15 years 8 months ago
The Statistical Learning of Accurate Heuristics
Heuristics used by search algorithms are usually composed of more primitive functions which we call "features". A method for combining features is presented which is bas...
Anna Bramanti-Gregor, Henry W. Davis
JSA
2006
97views more  JSA 2006»
15 years 6 months ago
Dynamic feature selection for hardware prediction
It is often possible to greatly improve the performance of a hardware system via the use of predictive (speculative) techniques. For example, the performance of out-of-order micro...
Alan Fern, Robert Givan, Babak Falsafi, T. N. Vija...
INFORMS
1998
100views more  INFORMS 1998»
15 years 6 months ago
Feature Selection via Mathematical Programming
The problem of discriminating between two nite point sets in n-dimensional feature space by a separating plane that utilizes as few of the features as possible, is formulated as a...
Paul S. Bradley, Olvi L. Mangasarian, W. Nick Stre...
176
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COGSCI
2010
99views more  COGSCI 2010»
15 years 6 months ago
Learning to Learn Causal Models
Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical B...
Charles Kemp, Noah D. Goodman, Joshua B. Tenenbaum
FECS
2006
208views Education» more  FECS 2006»
15 years 8 months ago
Integral Learning Pedagogical Technique and Distance Learning applied in Laboratory Classes for Electrical and Computing Enginee
- This paper presents the results of a PhD thesis research, with an innovative proposal for the development of a Technical Laboratory Disciplines in Electrical and Computing Engine...
Paulo Alves Garcia, José Sidnei Colombo Mar...