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» Evaluating learning algorithms and classifiers
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ICIP
2007
IEEE
16 years 6 months ago
Color Image Superresolution Based on a Stochastic Combinational Classification-Regression Algorithm
Abstract - The proposed algorithm in this work provides superresolution for color images by using a learning based technique that utilizes both generative and discriminant approach...
Karl S. Ni, Truong Q. Nguyen
NIPS
2008
15 years 5 months ago
Signal-to-Noise Ratio Analysis of Policy Gradient Algorithms
Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the e...
John W. Roberts, Russ Tedrake
ENC
2004
IEEE
15 years 8 months ago
A Method Based on Genetic Algorithms and Fuzzy Logic to Induce Bayesian Networks
A method to induce bayesian networks from data to overcome some limitations of other learning algorithms is proposed. One of the main features of this method is a metric to evalua...
Manuel Martínez-Morales, Ramiro Garza-Dom&i...
ICCV
2009
IEEE
16 years 9 months ago
Multiple Kernels for Object Detection
Our objective is to obtain a state-of-the art object category detector by employing a state-of-the-art image classifier to search for the object in all possible image subwindows....
Andrea Vedaldi, Varun Gulshan, Manik Varma, Andrew...
CVPR
2009
IEEE
16 years 11 months ago
Physics-based Edge Evaluation for Improved Color Constancy
Edge-based color constancy makes use of image derivatives to estimate the illuminant. However, different edge types exist in real-world images such as shadow, geometry, material...
Arjan Gijsenij (University of Amsterdam), Theo Gev...