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» On the Complexity of Function Learning
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86
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GECCO
2007
Springer
187views Optimization» more  GECCO 2007»
15 years 7 months ago
Defining implicit objective functions for design problems
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
Sean Hanna
ALT
1999
Springer
15 years 5 months ago
On the Uniform Learnability of Approximations to Non-Recursive Functions
Abstract. Blum and Blum (1975) showed that a class B of suitable recursive approximations to the halting problem is reliably EX-learnable. These investigations are carried on by sh...
Frank Stephan, Thomas Zeugmann
ICPR
2010
IEEE
15 years 3 months ago
Pattern Recognition Using Functions of Multiple Instances
The Functions of Multiple Instances (FUMI) method for learning a target prototype from data points that are functions of target and non-target prototypes is introduced. In this pa...
Alina Zare, Paul Gader
96
Voted
ICML
1997
IEEE
16 years 1 months ago
Robot Learning From Demonstration
The goal of robot learning from demonstration is to have a robot learn from watching a demonstration of the task to be performed. In our approach to learning from demonstration th...
Christopher G. Atkeson, Stefan Schaal
CVPR
2009
IEEE
16 years 7 months ago
Contextual Classification with Functional Max-Margin Markov Networks
We address the problem of label assignment in computer vision: given a novel 3-D or 2-D scene, we wish to assign a unique label to every site (voxel, pixel, superpixel, etc.). To...
Daniel Munoz, James A. Bagnell, Martial Hebert, Ni...