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ICANN
2010
Springer
15 years 4 months ago
Reinforcement Learning Based Neural Controllers for Dynamic Processes without Exploration
Abstract. In this paper we present a Reinforcement Learning (RL) approach with the capability to train neural adaptive controllers for complex control problems without expensive on...
Frank-Florian Steege, André Hartmann, Erik ...
ICCV
2009
IEEE
16 years 8 months ago
Constrained Clustering by Spectral Kernel Learning
Clustering performance can often be greatly improved by leveraging side information. In this paper, we consider constrained clustering with pairwise constraints, which specify s...
Zhenguo Li, Jianzhuang Liu
149
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CVPR
2003
IEEE
16 years 5 months ago
Object Class Recognition by Unsupervised Scale-Invariant Learning
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
Robert Fergus, Pietro Perona, Andrew Zisserman
CVPR
2008
IEEE
16 years 5 months ago
Latent topic random fields: Learning using a taxonomy of labels
An important problem in image labeling concerns learning with images labeled at varying levels of specificity. We propose an approach that can incorporate images with labels drawn...
Xuming He, Richard S. Zemel
MICCAI
2007
Springer
16 years 4 months ago
Active-Contour-Based Image Segmentation Using Machine Learning Techniques
Abstract. We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a c...
Patrick Etyngier, Florent Ségonne, Renaud K...