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ICONIP
2007
15 years 1 months ago
Using Generalization Error Bounds to Train the Set Covering Machine
In this paper we eliminate the need for parameter estimation associated with the set covering machine (SCM) by directly minimizing generalization error bounds. Firstly, we consider...
Zakria Hussain, John Shawe-Taylor
APIN
1998
132views more  APIN 1998»
14 years 11 months ago
Evolution-Based Methods for Selecting Point Data for Object Localization: Applications to Computer-Assisted Surgery
Object localization has applications in many areas of engineering and science. The goal is to spatially locate an arbitrarily-shaped object. In many applications, it is desirable ...
Shumeet Baluja, David Simon
ICML
2005
IEEE
16 years 18 days ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore
JSA
2006
97views more  JSA 2006»
14 years 11 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...
COGSCI
2002
108views more  COGSCI 2002»
14 years 11 months ago
Statistical models for the induction and use of selectional preferences
Selectional preferences have a long history in both generative and computational linguistics. However, since the publication of Resnik's dissertation in 1993, a new approach ...
Marc Light, Warren R. Greiff