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KAIS
2006
87views more  KAIS 2006»
13 years 10 months ago
Improving the performance of 1D object classification by using the Electoral College
Abstract It has been proven that districted matching schemes (e.g., the US presidential election scheme, also called the Electoral College) are more stable than undistricted matchi...
Liang Chen, Ruoyu Chen, Sharmin Nilufar
NECO
2008
129views more  NECO 2008»
13 years 10 months ago
Sparse Coding via Thresholding and Local Competition in Neural Circuits
While evidence indicates that neural systems may be employing sparse approximations to represent sensed stimuli, the mechanisms underlying this ability are not understood. We desc...
Christopher J. Rozell, Don H. Johnson, Richard G. ...
NAR
2006
77views more  NAR 2006»
13 years 10 months ago
SMART 5: domains in the context of genomes and networks
The Simple Modular Architecture Research Tool 10 (SMART) is an online resource (http://smart.embl. de/) used for protein domain identification and the analysis of protein domain a...
Ivica Letunic, Richard R. Copley, Birgit Pils, Ste...
TIP
2008
86views more  TIP 2008»
13 years 10 months ago
Learning the Dynamics and Time-Recursive Boundary Detection of Deformable Objects
We propose a principled framework for recursively segmenting deformable objects across a sequence of frames. We demonstrate the usefulness of this method on left ventricular segmen...
Walter Sun, Müjdat Çetin, Raymond C. C...
AI
1998
Springer
13 years 9 months ago
Worst-Case Analysis of the Perceptron and Exponentiated Update Algorithms
The absolute loss is the absolute difference between the desired and predicted outcome. This paper demonstrates worst-case upper bounds on the absolute loss for the Perceptron le...
Tom Bylander