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» Machine Learning by Function Decomposition
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CVPR
2008
IEEE
16 years 1 months ago
Learning for stereo vision using the structured support vector machine
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
Yunpeng Li, Daniel P. Huttenlocher
ICIP
2008
IEEE
16 years 1 months ago
Supervised image segmentation via ground truth decomposition
This paper proposes a data driven image segmentation algorithm, based on decomposing the target output (ground truth). Classical pixel labeling methods utilize machine learning al...
Ilya Levner, Russell Greiner, Hong Zhang
ICANN
2001
Springer
15 years 4 months ago
Incremental Support Vector Machine Learning: A Local Approach
Abstract. In this paper, we propose and study a new on-line algorithm for learning a SVM based on Radial Basis Function Kernel: Local Incremental Learning of SVM or LISVM. Our meth...
Liva Ralaivola, Florence d'Alché-Buc
ICML
2003
IEEE
16 years 18 days ago
Hidden Markov Support Vector Machines
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines an...
Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofm...
ICMLA
2010
14 years 9 months ago
Multi-Agent Inverse Reinforcement Learning
Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...
Sriraam Natarajan, Gautam Kunapuli, Kshitij Judah,...