A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Filters
Efficient Geometric-based Computation of the String Subsequence Kernel
[article]
2015
arXiv
pre-print
Preserved Fulltext
In this paper, we present a novel Geometric-based approach to compute efficiently the string subsequence kernel (SSK). Our main idea is that the SSK computation reduces to range query problem. ...
Kernel methods are powerful tools in machine learning. They have to be computationally efficient. ...
In the literature, there are variants of trie-based string subsequence kernels. For instance the (p, m)-mismatch string kernel [5] and restricted SSK [8] . ...
arXiv:1502.07776v1
fatcat:pg5yndbj6zfszdo64mgdylco4a
THE SPECTRUM KERNEL: A STRING KERNEL FOR SVM PROTEIN CLASSIFICATION
2001
Biocomputing 2002
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Our experiments provide evidence that string-based kernels, in conjunction with SVMs, could offer a viable and computationally efficient alternative to other methods of protein classification and homology ...
Our kernel is conceptually simple and efficient to compute and, in experiments on the SCOP database, performs well in comparison with state-ofthe-art methods for homology detection. ...
Acknowledgments: WSN is supported by an Award in Bioinformatics from the PhRMA Foundation, and by National Science Foundation grants DBI-0078523 and ISI-0093302. ...
doi:10.1142/9789812799623_0053
fatcat:osz77hava5b7ppb2dzzv25wcty
Applications of alignment-free methods in epigenomics
2013
Briefings in Bioinformatics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Computational studies using these methods have provided important insights into the epigenetic regulatory mechanisms. . ...
His research is focused on new computational approaches to investigate different epigenetic factors that regulate the chromatin structure and dynamics. Giosue' ...
Easy to interpret SVM/kernel based O(m 3 ) for the QP solver and O(k(n)) for the computation of the kernel matrix, where k(n) is the computational cost of the kernel used Yes
No
at Harvard Library ...
doi:10.1093/bib/bbt078
pmid:24197932
pmcid:PMC4017331
fatcat:d47gpaahijdzfimn6dq5a64io4
Tree Planar Languages
2007
Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
The position in the Chomsky hierarchy of any class of planar languages depends on the particular kernel it is based on. ...
They are based on hyperplanes in a feature space associated with a string kernel, which corresponds to a set of linear equalities over features. ...
Jean Monnet, St Etienne, France, funded by the IST Programme of the EU, under the PASCAL Network of Excellence. I would also like to thank Colin de la Higuera for stimulating discussions. ...
doi:10.1109/icdmw.2007.82
dblp:conf/icdm/Florencio07
fatcat:4hxpyexajbc2hjfe2r3zwjubgu
Planar Languages and Learnability
[chapter]
2006
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2010; you can also visit the original URL.
The file type is application/pdf.
In this paper we show that using techniques from kernel-based learning, we can represent and efficiently learn, from positive data alone, various linguistically interesting context-sensitive languages. ...
We demonstrate the polynomial-time identifiability in the limit of these classes, and discuss some language theoretic properties of these classes, and their relationship to the choice of kernel/feature ...
Acknowledgements This work has benefitted from the support of the EU funded PASCAL Network of Excellence on Pattern Analysis, Statistical Modelling and Computational Learning. ...
doi:10.1007/11872436_13
fatcat:6mwwtt2monht5crwbzduo46dwu
svcR: An R Package for Support Vector Clustering improved with Geometric Hashing applied to Lexical Pattern Discovery
[article]
2015
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Secondly we showed that this SVC approach using a Jaccard-Radial base kernel can help to classify well enough a set of terms into ontological classes and help to define regular expression rules for information ...
In this sense, SVC can be seen as an efficient cluster extraction if clusters are separable in a 2-D map. ...
The methodology discussed in this paper has been supported by the INRA-1077-SE grant from the French Institute for Agricultural Research (agriculture, food & nutrition, environment and basic biology). ...
arXiv:1504.06080v1
fatcat:nz5uj6i23ndgzm7knx3w7xwigq
Finite element analysis in situ
2011
Finite elements in analysis and design
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
The advantages of this approach include unmatched flexibility in handling geometric errors, small features, complex boundary conditions, and interfaces, while maintaining most of the benefits of classical ...
It can be applied to any geometric model and used within any geometric modeling system that supports two fundamental queries: point membership testing and distance to boundary computation. ...
Acknowledgments This research is supported in part by the National Science Foundation Grants CMMI-0621116, CMMI-0856778, CMMI-0900219 and CMMI-1042211. ...
doi:10.1016/j.finel.2011.03.001
fatcat:xnhdg5i5mfdhhmoaotyykwrqq4
Predicting flexible length linear B-cell epitopes
2008
Computational systems bioinformatics. Computational Systems Bioinformatics Conference
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Based on our empirical comparisons, we propose FBCPred, a novel method for predicting flexible length linear B-cell epitopes using the subsequence kernel. ...
The first approach utilizes four sequence kernels for determining a similarity score between any arbitrary pair of variable length sequences. ...
Acknowledgments This work was supported in part by a doctoral fellowship from the Egyptian Government to Yasser EL-Manzalawy and a grant from the National Institutes of Health (GM066387) to Vasant Honavar ...
pmid:19642274
pmcid:PMC3400678
fatcat:nb6jdbej5zbvlpy2dvtwzmxaxi
3DString
2006
Proceedings of the 15th ACM international conference on Information and knowledge management - CIKM '06
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2008; you can also visit the original URL.
The file type is application/pdf.
We define a similarity measure on these feature strings that counts common k-mers in two input strings, which is referred to as the spectrum kernel in the field of kernel methods. ...
We prove that on our feature strings, this similarity measure can be computed in time linear to the number of different characters in these strings. ...
This procedure recursively turns all k-mers based on three or more characters into k-mers of two different characters, which can be computed efficiently as described above. ...
doi:10.1145/1183614.1183647
dblp:conf/cikm/AssfalgBK06
fatcat:cmiqi6da2bcp3kcaag3om6vgvq
Edit distance-based kernel functions for structural pattern classification
2006
Pattern Recognition
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
The validity of the kernel method cannot be established for edit distance in general. ...
The proposed approach is applicable to both string and graph representations of patterns. ...
The authors would also like to thank Barbara Spillmann for preparing the string datasets, and Dr. Jens Gregor for making the Chromosome dataset available. ...
doi:10.1016/j.patcog.2006.04.012
fatcat:r6kxeeq4t5exlk3otepkudeznm
Fast Organization of Large Photo Collections Using CUDA
[chapter]
2012
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2010; you can also visit the original URL.
The file type is application/pdf.
By leveraging the inherent parallelism of the problem and through the use of efficient GPU-based algorithms, our system is able to effectively summarize datasets containing up to three million images in ...
To our knowledge, this is the first approach that tackles this problem exclusively through the use of general-purpose GPU computing techniques. ...
To ensure high computational performance, our technique employs the highly optimized CUBLAS library, with the exception of a kernel for converting float vectors into binary strings. ...
doi:10.1007/978-3-642-35740-4_36
fatcat:pfan6bhkirhf3ccpoq6kh6v47q
String kernels for protein sequence comparisons: improved fold recognition
2017
BMC Bioinformatics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Results: In this study, we develop an alignment free alternative to these methods that is based on the concept of string kernels. ...
Starting from recently proposed kernels on the discrete space of protein sequences (Shen et al, Found. Comput. Math., 2013,14:951-984), we introduce our own version, SeqKernel. ...
Availability of data and materials The program SeqKernel described in the paper, as well as all the datasets of sequences used in this study are available from the authors upon request. ...
doi:10.1186/s12859-017-1560-9
pmid:28245816
pmcid:PMC5331664
fatcat:e3zpttxxnjeo3pu6kdrxsdvwku
Predicting linear B‐cell epitopes using string kernels
2008
Journal of Molecular Recognition
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Based on the results of our computational experiments, we propose BCPred, a novel method for predicting linear B-cell epitopes using the subsequence kernel. ...
We show that the predictive performance of BCPred (AUC = 0.758) outperforms 11 SVM-based classifiers developed and evaluated in our experiments as well as our implementation of AAP (AUC = 0.7), a recently ...
Acknowledgements We thank the anonymous reviewers for their comments and suggestions, Dr. Janez Dems ar for discussing the applicability of non-parametric tests, Dr. ...
doi:10.1002/jmr.893
pmid:18496882
pmcid:PMC2683948
fatcat:mv64qg3u7bggpn25v5oslvwgtm
PREDICTING FLEXIBLE LENGTH LINEAR B-CELL EPITOPES
2008
Computational Systems Bioinformatics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2008; you can also visit the original URL.
The file type is application/pdf.
Based on our empirical comparisons, we propose FBCPred, a novel method for predicting flexible length linear B-cell epitopes using the subsequence kernel. ...
The first approach utilizes four sequence kernels for determining a similarity score between any arbitrary pair of variable length sequences. ...
Acknowledgments This work was supported in part by a doctoral fellowship from the Egyptian Government to Yasser EL-Manzalawy and a grant from the National Institutes of Health (GM066387) to Vasant Honavar ...
doi:10.1142/9781848162648_0011
fatcat:fr7xdueuybh5vjozubkb2r3ewa
Efficient Algorithms for Similarity Measures over Sequential Data: A Look Beyond Kernels
[chapter]
2006
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2007; you can also visit the original URL.
The file type is application/pdf.
This contribution addresses the efficient computation of distance functions and similarity coefficients for sequential data. ...
Two proposed algorithms utilize different data structures for efficient computation and yield a runtime linear in the sequence length. ...
Acknowledgments The authors gratefully acknowledge the funding from Bundesministerium für Bildung und Forschung under the project MIND (FKZ 01-SC40A) and would like to thank Sören Sonnenburg, Julian Laub ...
doi:10.1007/11861898_38
fatcat:3oankd3oqraafakv63zqgaizmm
« Previous
Showing results 1 — 15 out of 6,168 results