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Chia-Kai's AMMAI

Saturday, June 7, 2008. Reading] Support vector learning for ordinal regression. This paper extends the SVM framework for the ordinal regression (classification of ordered classes). The algorithm is easy to understand after the problem is formulated. The key contribution of the paper is showing that the ordinal regression problem can be transformed into regular SVR by using the difference of the feature vectors as the new feature vector. Also the error bound of the algorithm is presented. This paper pres...

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Chia-Kai's AMMAI | ckammai.blogspot.com Reviews

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Saturday, June 7, 2008. Reading] Support vector learning for ordinal regression. This paper extends the SVM framework for the ordinal regression (classification of ordered classes). The algorithm is easy to understand after the problem is formulated. The key contribution of the paper is showing that the ordinal regression problem can be transformed into regular SVR by using the difference of the feature vectors as the new feature vector. Also the error bound of the algorithm is presented. This paper pres...

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Chia-Kai's AMMAI | ckammai.blogspot.com Reviews

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Saturday, June 7, 2008. Reading] Support vector learning for ordinal regression. This paper extends the SVM framework for the ordinal regression (classification of ordered classes). The algorithm is easy to understand after the problem is formulated. The key contribution of the paper is showing that the ordinal regression problem can be transformed into regular SVR by using the difference of the feature vectors as the new feature vector. Also the error bound of the algorithm is presented. This paper pres...

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Chia-Kai's AMMAI: March 2008

http://ckammai.blogspot.com/2008_03_01_archive.html

Sunday, March 30, 2008. Reading] Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary. This paper presents a new concept to object recognition: model it as a machine translation problem. In EM, Lagrangian is used to make sure the variables are sum-to-one. However, maybe a simple re-projection is enough. And in fact, re-projection is indeed used in the algorithm (Fig. 4).can't see the Lagrangian multipliers in the code @ . Friday, March 28, 2008. Also the running time...

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Chia-Kai's AMMAI: [Reading] On Spectral Clustering: Analysis and An Algorithm

http://ckammai.blogspot.com/2008/05/reading-on-spectral-clustering-analysis.html

Tuesday, May 13, 2008. Reading] On Spectral Clustering: Analysis and An Algorithm. This paper presents a simple algorithm of clustering, based on the spectral theory. Compare with other spectral clustering methods (such as normalized cut), the algorithm is much easier to understand and implement. The key idea is that, unlike previous methods, many eigenvectors are used instead of only one. In summary, I seldom like the papers from NIPS.too hard for me. Subscribe to: Post Comments (Atom).

3

Chia-Kai's AMMAI: [Reading] Mining Association Rules between Sets of Items in Large Databases

http://ckammai.blogspot.com/2008/05/reading-mining-association-rules.html

Sunday, May 25, 2008. Reading] Mining Association Rules between Sets of Items in Large Databases. This paper presents a system to find the association rules from a large number of transaction records. At the time of publication, the problem and the solution of this field might be very twilit and this should be a very pioneering work. Subscribe to: Post Comments (Atom). I'm a software engineer at Google, previously at Lytro, Nokia research center, and National Taiwan University. View my complete profile.

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Chia-Kai's AMMAI: [Reading] An Introduction to Graphical Models

http://ckammai.blogspot.com/2008/04/reading-introduction-to-graphical.html

Tuesday, April 29, 2008. Reading] An Introduction to Graphical Models. This is a very good introduction paper for the graphical model. It elegantly explains why and when we should use the graphical model, what operations are usually used in the graphical model (so you may map your problem into one of them), and what tools are available to run these operations efficiently. Very impressed for your talk today. :) No doubt to be named "SIGGRAPH" Liang. May 6, 2008 at 8:22 PM. View my complete profile.

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Chia-Kai's AMMAI: [Reading] Support vector learning for ordinal regression

http://ckammai.blogspot.com/2008/06/reading-support-vector-learning-for.html

Saturday, June 7, 2008. Reading] Support vector learning for ordinal regression. This paper extends the SVM framework for the ordinal regression (classification of ordered classes). The algorithm is easy to understand after the problem is formulated. The key contribution of the paper is showing that the ordinal regression problem can be transformed into regular SVR by using the difference of the feature vectors as the new feature vector. Also the error bound of the algorithm is presented.

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Chia-Kai's AMMAI

Saturday, June 7, 2008. Reading] Support vector learning for ordinal regression. This paper extends the SVM framework for the ordinal regression (classification of ordered classes). The algorithm is easy to understand after the problem is formulated. The key contribution of the paper is showing that the ordinal regression problem can be transformed into regular SVR by using the difference of the feature vectors as the new feature vector. Also the error bound of the algorithm is presented. This paper pres...

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