New PDF release: Advances in Intelligent Data Analysis VII: 7th International

By Jaakko Hollmén, Jarkko Tikka (auth.), Michael R. Berthold, John Shawe-Taylor, Nada Lavrač (eds.)

ISBN-10: 3540748245

ISBN-13: 9783540748243

Weareproudtopresenttheproceedingsoftheseventhbiennialconferenceinthe clever information research sequence. The convention came about in Ljubljana, Slo- nia, September 6-8, 2007. IDA keeps to extend its scope, caliber and measurement. It begun as a small side-symposium as a part of a bigger convention in 1995 in Baden-Baden(Germany).It fast attractedmoreinterest in either submissions and attendance because it moved to London (1997) after which Amsterdam (1999). the subsequent 3 conferences have been held in Lisbon (2001), Berlin (2003) after which Madrid in 2005. The enhancing caliber of the submissions has enabled the organizers to collect courses of ever-increasing consistency and caliber. This yr we madea rigorousselectionof33papersoutofalmost100submissions.Theresu- ing oral shows have been then scheduled in a single-track, two-and-a-half-day convention application, summarized within the booklet that you've sooner than you. in response to the said IDA target of “bringing jointly researchers from various disciplines,” we think we've got completed a superb stability of presentationsfromthemoretheoretical–bothstatisticalandmachinelearning– to the extra application-oriented components that illustrate how those recommendations can beusedinpractice.Forexample,theproceedingsincludepaperswiththeoretical contributions facing statistical ways to series alignment in addition to papers addressing sensible difficulties within the components of textual content classi?cation and scientific information research. it truly is reassuring to work out that IDA maintains to convey such assorted parts jointly, hence assisting to cross-fertilize those ?elds.

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Extra resources for Advances in Intelligent Data Analysis VII: 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007. Proceedings

Sample text

If these symbols are equal, we call this a match. If they are not equal, this is a mismatch. If one of the symbols is a −, this is called an indel or a gap. With each possible match, substitution or gap at position i, a score is attached. To quantify these scores, three score parameters can be used, one corresponding to a match (αm ), one to a mismatch (αs ), and one to a gap (αg ). The score of the global alignment can be expressed as a linear function of these parameters: φ (S1 , S2 , A) = αm m + αs s + αg g = αT x where we have defined the vectors αT = [αm αs αg ] and xT = [m s g] and m, s and g represent the number of matches, mismatches and gaps in the alignment.

To manage the extremely high dimensionality of the feature space, we exploited the nonnegativity and sparseness of the feature vectors. In particular, by careful bookkeeping, it is possible to implement the multiplicative updates for L1 –regularized linear regression without having to construct or store the matrix A in eq. (7). Also, we only used multiplicative updates to solve the primal optimizations for L1 –regularized IRLS sub-problems: the dual optimizations were not constructed. The weight vectors were initialized from the results of unregularized logistic regressions, performed by limited-memory quasi-Newton methods (L-BFGS).

1. (a) Test error as function of the training set size. (b) Distribution of correctly reconstructed alignments as a function of the number of additional constraints. Finally we assess the effectiveness of the proposed method on real sequences of amino acids. We perform experiments similar to those presented in the paper of Kececioglu et al. [6]. We consider five multiple alignments from the PALI database [1] of structural protein alignments: T-boxes (box), NADH oxidoreductases (nad), Kunitz inhibitors (kun), Sir2 transcription regulators (sir) and Learning to Align: A Statistical Approach 33 pectin methylesterases (pec).

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Advances in Intelligent Data Analysis VII: 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007. Proceedings by Jaakko Hollmén, Jarkko Tikka (auth.), Michael R. Berthold, John Shawe-Taylor, Nada Lavrač (eds.)


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