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» Structured metric learning for high dimensional problems
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ECML
2006
Springer
15 years 1 months ago
Scaling Model-Based Average-Reward Reinforcement Learning for Product Delivery
Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
Scott Proper, Prasad Tadepalli
ESANN
2006
14 years 11 months ago
Visual Data Mining and Machine Learning
Information visualization and visual data mining leverage the human visual system to provide insight and understanding of unorganized data. In order to scale to massive sets of hig...
Fabrice Rossi
CVPR
2008
IEEE
15 years 11 months ago
Re-thinking non-rigid structure from motion
We present a novel approach to non-rigid structure from motion (NRSFM) from an orthographic video sequence, based on a new interpretation of the problem. Existing approaches assum...
Vincent Rabaud, Serge Belongie
GRC
2010
IEEE
14 years 10 months ago
Learning Multiple Latent Variables with Self-Organizing Maps
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
Lili Zhang, Erzsébet Merényi
BMVC
2010
14 years 7 months ago
High Five: Recognising human interactions in TV shows
In this paper we address the problem of recognising interactions between two people in realistic scenarios for video retrieval purposes. We develop a per-person descriptor that us...
Alonso Patron, Marcin Marszalek, Andrew Zisserman,...