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» Prediction on Spike Data Using Kernel Algorithms
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JCP
2008
167views more  JCP 2008»
14 years 9 months ago
Accelerated Kernel CCA plus SVDD: A Three-stage Process for Improving Face Recognition
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
Ming Li, Yuanhong Hao
66
Voted
GECCO
2003
Springer
139views Optimization» more  GECCO 2003»
15 years 2 months ago
Daily Stock Prediction Using Neuro-genetic Hybrids
We propose a neuro-genetic daily stock prediction model. Traditional indicators of stock prediction are utilized to produce useful input features of neural networks. The genetic al...
Yung-Keun Kwon, Byung Ro Moon
EGITALY
2006
14 years 11 months ago
3D Data Segmentation Using a Non-Parametric Density Estimation Approach
In this paper, a new segmentation approach for sets of 3D unorganized points is proposed. The method is based on a clustering procedure that separates the modes of a non-parametri...
Umberto Castellani, Marco Cristani, Vittorio Murin...
ICML
2004
IEEE
15 years 10 months ago
Unifying collaborative and content-based filtering
Collaborative and content-based filtering are two paradigms that have been applied in the context of recommender systems and user preference prediction. This paper proposes a nove...
Justin Basilico, Thomas Hofmann
CVPR
2012
IEEE
13 years 3 days ago
Geodesic flow kernel for unsupervised domain adaptation
In real-world applications of visual recognition, many factors—such as pose, illumination, or image quality—can cause a significant mismatch between the source domain on whic...
Boqing Gong, Yuan Shi, Fei Sha, Kristen Grauman