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» Variations on U-Shaped Learning
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CEC
2008
IEEE
14 years 1 months ago
Learning what to ignore: Memetic climbing in topology and weight space
— We present the memetic climber, a simple search algorithm that learns topology and weights of neural networks on different time scales. When applied to the problem of learning ...
Julian Togelius, Faustino J. Gomez, Jürgen Sc...
ICANN
2005
Springer
14 years 28 days ago
Action Understanding and Imitation Learning in a Robot-Human Task
We report results of an interdisciplinary project which aims at endowing a real robot system with the capacity for learning by goaldirected imitation. The control architecture is b...
Wolfram Erlhagen, Albert Mukovskiy, Estela Bicho, ...
ICPR
2000
IEEE
13 years 11 months ago
Handwritten Character Segmentation Using Transformation-Based Learning
This paper presents a character segmentation algorithm for unconstrained cursive handwritten text. The transformation-based learning method and a simplified variation of it are us...
Ergina Kavallieratou, Efstathios Stamatatos, Nikos...
JMLR
2012
11 years 9 months ago
Lifted coordinate descent for learning with trace-norm regularization
We consider the minimization of a smooth loss with trace-norm regularization, which is a natural objective in multi-class and multitask learning. Even though the problem is convex...
Miroslav Dudík, Zaïd Harchaoui, J&eacu...
CORR
2010
Springer
141views Education» more  CORR 2010»
13 years 6 months ago
Learning Functions of Few Arbitrary Linear Parameters in High Dimensions
Let us assume that f is a continuous function defined on the unit ball of Rd , of the form f(x) = g(Ax), where A is a k×d matrix and g is a function of k variables for k ≪ d. ...
Massimo Fornasier, Karin Schnass, Jan Vybír...