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101
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ICML
2004
IEEE
16 years 3 months ago
A comparative study on methods for reducing myopia of hill-climbing search in multirelational learning
Hill-climbing search is the most commonly used search algorithm in ILP systems because it permits the generation of theories in short running times. However, a well known drawback...
Lourdes Peña Castillo, Stefan Wrobel
ATAL
2009
Springer
15 years 9 months ago
Adaptive learning in evolving task allocation networks
In this paper, we study multi-agent economic systems using a recent approach to economic modeling called Agent-based Computational Economics (ACE): the application of the Complex ...
Tomas Klos, Bart Nooteboom
127
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NIPS
2001
15 years 4 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona
CVPR
2008
IEEE
16 years 4 months ago
Learning 4D action feature models for arbitrary view action recognition
In this paper we present a novel approach using a 4D (x,y,z,t) action feature model (4D-AFM) for recognizing actions from arbitrary views. The 4D-AFM elegantly encodes shape and m...
Pingkun Yan, Saad M. Khan, Mubarak Shah
AAAI
2007
15 years 5 months ago
Acquiring Visibly Intelligent Behavior with Example-Guided Neuroevolution
Much of artificial intelligence research is focused on devising optimal solutions for challenging and well-defined but highly constrained problems. However, as we begin creating...
Bobby D. Bryant, Risto Miikkulainen