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» Neural methods for non-standard data
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ICANN
2007
Springer
15 years 8 months ago
Resilient Approximation of Kernel Classifiers
Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...
Thorsten Suttorp, Christian Igel
JCNS
2010
103views more  JCNS 2010»
14 years 10 months ago
Efficient computation of the maximum a posteriori path and parameter estimation in integrate-and-fire and more general state-spa
A number of important data analysis problems in neuroscience can be solved using state-space models. In this article, we describe fast methods for computing the exact maximum a pos...
Shinsuke Koyama, Liam Paninski
148
Voted
ICASSP
2011
IEEE
14 years 7 months ago
Sparse common spatial patterns in brain computer interface applications
The Common Spatial Pattern (CSP) method is a powerful technique for feature extraction from multichannel neural activity and widely used in brain computer interface (BCI) applicat...
Fikri Goksu, Nuri Firat Ince, Ahmed H. Tewfik
IWANN
2007
Springer
15 years 10 months ago
A Novel 2-D Model Approach for the Prediction of Hourly Solar Radiation
In this work, a two-dimensional (2-D) representation of the hourly solar radiation data is proposed. The model enables accurate forecasting using image prediction methods. One year...
Fatih Onur Hocaoglu, Ömer Nezih Gerek, Mehmet...
DATAMINE
2006
224views more  DATAMINE 2006»
15 years 4 months ago
Characteristic-Based Clustering for Time Series Data
With the growing importance of time series clustering research, particularly for similarity searches amongst long time series such as those arising in medicine or finance, it is cr...
Xiaozhe Wang, Kate A. Smith, Rob J. Hyndman