Filters








3,399 Hits in 4.6 sec

Graph-Based Learning via Auto-Grouped Sparse Regularization and Kernelized Extension

Yuqiang Fang, Ruili Wang, Bin Dai, Xindong Wu
<span title="">2015</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ht3yl6qfebhwrg7vrxkz4gxv3q" style="color: black;">IEEE Transactions on Knowledge and Data Engineering</a> </i> &nbsp;
The key task in developing graph-based learning algorithms is constructing an informative graph to express the contextual information of a data manifold.  ...  Index Terms-Graph based learning, sparse representation, spectral embedding, subspace learning, non-negative matrix factorization Y. Fang and B. Dai are with the College  ...  Spectral Embedding In this experiment, we compare our GS-graph based spectral embedding algorithm with Laplacian Eigenmaps and the ' 1 -graph based spectral embedding algorithm.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tkde.2014.2312322">doi:10.1109/tkde.2014.2312322</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/w3nqibytxzgyzfvs2kusdzjbbq">fatcat:w3nqibytxzgyzfvs2kusdzjbbq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170506023943/http://www.massey.ac.nz/~rwang/publications/14-TKDE-Fang.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c1/cc/c1ccd186038c7d48111fcd37cfee668e335277c8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tkde.2014.2312322"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Margin Based Semi-Supervised Elastic Embedding for Face Image Analysis

F. Dornaika, Y. El Traboulsi
<span title="">2017</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6s36fqp6q5hgpdq2scjq3sfu6a" style="color: black;">2017 IEEE International Conference on Computer Vision Workshops (ICCVW)</a> </i> &nbsp;
This paper introduces a graph-based semi-supervised elastic embedding method as well as its kernelized version for face image embedding and classification.  ...  are based on label propagation or graph-based semi-supervised embedding.  ...  More precisely, we propose a graph-based semi-supervised elastic embedding as well as its kernelized version.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccvw.2017.156">doi:10.1109/iccvw.2017.156</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/iccvw/DornaikaT17.html">dblp:conf/iccvw/DornaikaT17</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pbmr2pz5erd27f5skd2xhw2c3e">fatcat:pbmr2pz5erd27f5skd2xhw2c3e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200319040624/http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w21/Dornaika_Margin_Based_Semi-Supervised_ICCV_2017_paper.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b2/62/b262a00574e73917bf39f3e778bb431e3ad45175.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccvw.2017.156"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Kernel sparse representation for time series classification

Zhihua Chen, Wangmeng Zuo, Qinghua Hu, Liang Lin
<span title="">2015</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ozlq63ehnjeqxf6cuxxn27cqra" style="color: black;">Information Sciences</a> </i> &nbsp;
In recent years, a class of sparse representation based classifiers (SRC) [42, 51] and collaborative representation based classifiers (CRC) [52] have been developed.  ...  Recently, Chen et al. [6] introduced a method called edit distance with real penalty (ERP) and Marteau [34] proposed an alignment-based distance metric, called time warp edit distance (TWED).  ...  Based on the Gaussian elastic matching kernel, a kernel SRC model together with a kernel OMP algorithm was proposed.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.ins.2014.08.066">doi:10.1016/j.ins.2014.08.066</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/y7dmuk37nzh25gnqqzn27i5lyy">fatcat:y7dmuk37nzh25gnqqzn27i5lyy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20161021010246/http://ss.sysu.edu.cn:80/~ll/files/is2014_timeseriesclassification.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d1/d7/d1d7d15659dcd9b9c27ed16e7a4dc4bbcc652c87.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.ins.2014.08.066"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Breast image feature learning with adaptive deconvolutional networks

Andrew R. Jamieson, Karen Drukker, Maryellen L. Giger, Bram van Ginneken, Carol L. Novak
<span title="2012-02-23">2012</span> <i title="SPIE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xfwg4fmybzazfktmdtzvhcujka" style="color: black;">Medical Imaging 2012: Computer-Aided Diagnosis</a> </i> &nbsp;
Non-linear, local structure preserving dimension reduction, Elastic Embedding (Carreira-Perpiñán, 2010), was then used to visualize the SPM kernel output in 2D and qualitatively inspect image relationships  ...  explored the use of Adaptive Deconvolutional Networks (ADN) for learning high-level features in diagnostic breast mass lesion images with potential application to computer-aided diagnosis (CADx) and content-based  ...  Figure 7 displays an example of one such visualization based on the unsupervised Elastic Embedding 6 DR, for a random sub-set sample (270 cases) from the entire US data set.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.910710">doi:10.1117/12.910710</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/micad/JamiesonDG12.html">dblp:conf/micad/JamiesonDG12</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/25h5a4zfe5dizlnrdse4vfgyua">fatcat:25h5a4zfe5dizlnrdse4vfgyua</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20130804224346/http://home.uchicago.edu:80/%7Eandrewj/Publications/Jamieson_SPIE_2012_MANUSCRIPT_Final_uploadv2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/2a/f0/2af092f512f6895397dc5ce6146b2eb65b286052.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.910710"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Study of Different Face Recognition Algorithms and Challenges

Uma Shankar Kurmi, Dheeraj Agrawal, R. K. Baghel
<span title="2014-02-01">2014</span> <i title="Diva Enterprises Private Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ovxaom4acnhdnchlnp5no7hba4" style="color: black;">International Journal of Engineering Research</a> </i> &nbsp;
This paper presents some algorithms for face recognition.  ...  Discriminant Analysis (LDA) or Principal Components Analysis (PCA) is used to get better recognition results.  ...  For example, feature-based matching is used to extract relative position and distance features. Automatic detection of features used to develop a face recognition algorithm by Kanade [7].  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.17950/ijer/v3s2/216">doi:10.17950/ijer/v3s2/216</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7dgirjgrcvdddnemllzo4sm5qe">fatcat:7dgirjgrcvdddnemllzo4sm5qe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170811172300/http://www.ijer.in/ijer/publication/v3s2/IJER_2014_216.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/49/60/49600d98d45292a7bd8d4b7626feb00e22ff6768.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.17950/ijer/v3s2/216"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Adaptive Down-Sampling and Dimension Reduction in Time Elastic Kernel Machines for Efficient Recognition of Isolated Gestures [chapter]

Pierre-Francois Marteau, Sylvie Gibet, Clément Reverdy
<span title="2016-11-04">2016</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/oqt3yqhkxvcubnonwg57er4tdq" style="color: black;">Studies in Computational Intelligence</a> </i> &nbsp;
Elastic and Euclidean kernels are then compared through support vector machine learning.  ...  Yet this is a major issue when considering the use of elastic distances which are characterized by a quadratic complexity along the time axis.  ...  Furthermore, the elasticity of the kernel provides a significant performance gain (comparatively to kernel based on the Euclidean distance) which is very important when the data are characterized by high  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-45763-5_3">doi:10.1007/978-3-319-45763-5_3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rq3amanpurc7lbp25c2nqa2caa">fatcat:rq3amanpurc7lbp25c2nqa2caa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180726091059/https://hal.archives-ouvertes.fr/hal-01401453/document" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/53/0e/530e65ee380d12b92d8614d8baeb9cdbf1be9701.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-45763-5_3"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

A review on distance based time series classification [article]

Amaia Abanda, Usue Mori, Jose A. Lozano
<span title="2018-06-12">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In other cases, the distances are employed to obtain a time series kernel and enable the use of kernel methods for time series classification.  ...  The particularity of the data makes it a challenging task and different approaches have been taken, including the distance based approach. 1-NN has been a widely used method within distance based time  ...  The proposed method uses the AdaBoost [44] algorithm, which is able to select discriminative prototypes and combine a set of weak learners.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1806.04509v1">arXiv:1806.04509v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5kg73nvf3nexxgp6cwt5pma544">fatcat:5kg73nvf3nexxgp6cwt5pma544</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200826021858/https://arxiv.org/pdf/1806.04509v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ff/5c/ff5ce846e72583c5b497135c1b9f01a506bf0bd5.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1806.04509v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Sparse Graph Embedding Based on the Fuzzy Set for Image Classification

Minghua Wan, Mengting Ge, Tianming Zhan, Zhangjing Yang, Hao Zheng, Guowei Yang, Jianxin Li
<span title="2021-01-16">2021</span> <i title="Hindawi Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/y3fh56bfunh5fgneywwba6d4ke" style="color: black;">Complexity</a> </i> &nbsp;
Finally, the optimal discriminative sparse projection matrix is obtained by adding elastic network regression.  ...  In recent years, many face image feature extraction and dimensional reduction algorithms have been proposed for linear and nonlinear data, such as local-based graph embedding algorithms or fuzzy set algorithms  ...  In order to solve the above problems, we study the LGE algorithm based on subspace learning, elastic network regression, and fuzzy set theory, namely, sparse graph embedding with fuzzy set for image classification  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2021/6638985">doi:10.1155/2021/6638985</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/thebaq2ezfeklodvfmht4cexdy">fatcat:thebaq2ezfeklodvfmht4cexdy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210715024437/https://downloads.hindawi.com/journals/complexity/2021/6638985.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ed/21/ed21888699390bedbcbcb4a7e9a0e00f4a333e89.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2021/6638985"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> hindawi.com </button> </a>

Soft Computing Techniques Based Image Classification using Support Vector Machine Performance

Tarun Jaiswal, Dr. S. Jaiswal, Dr. Ragini Shukla
<span title="2019-04-30">2019</span> <i title="South Asia Management Association"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/oarwpnpqjjfbbkyptszxdp4ch4" style="color: black;">International Journal of Trend in Scientific Research and Development</a> </i> &nbsp;
In this paper we compare different kernel had been developed for support vector machine based time series classification.  ...  In this paper, by spreading the Gaussian RBF kernel by Gaussian elastic metric kernel. Gaussian elastic metric kernel is extended version of Gaussian RBF.  ...  Most importantly, the kernel contains all of the information about the relative positions of the inputs in the feature space and the actual learning algorithm is based only on the kernel function and can  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.31142/ijtsrd23437">doi:10.31142/ijtsrd23437</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/em7ydbsaq5bvlcqt63jid4rpbu">fatcat:em7ydbsaq5bvlcqt63jid4rpbu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200319024317/https://www.ijtsrd.com/papers/ijtsrd23437.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/40/46/4046d1a96e6e984b9978517ced0eb693f88b34c8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.31142/ijtsrd23437"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Logistic Regression Based on Statistical Learning Model with Linearized Kernel for Classification

Xiaochun Guan, Jianhua Zhang, Shengyong Chen
<span title="">2021</span> <i title="Central Library of the Slovak Academy of Sciences"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rsgu6oqy7fcfdl4hs633t7yefy" style="color: black;">Computing and informatics</a> </i> &nbsp;
Using a generalized linear model, the elastic net regularization is adopted to explore the grouping effect of the linearized kernel feature space.  ...  In this paper, we propose a logistic regression classification method based on the integration of a statistical learning model with linearized kernel preprocessing.  ...  They introduce a preprocessing stage based on the kernel method for the dictionary learning algorithm.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.31577/cai_2021_2_298">doi:10.31577/cai_2021_2_298</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/js7skprzzbf4ze5zwps2ufdfyy">fatcat:js7skprzzbf4ze5zwps2ufdfyy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211016134546/http://www.cai.sk/ojs/index.php/cai/article/download/2021_2_298/1084" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c9/a7/c9a76c8a2b0506a8778b36b4ffec834cb1afbe20.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.31577/cai_2021_2_298"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Approximate Orthogonal Sparse Embedding for Dimensionality Reduction

Zhihui Lai, Wai Keung Wong, Yong Xu, Jian Yang, David Zhang
<span title="">2016</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/j6amxna35bbs5p42wy5crllu2i" style="color: black;">IEEE Transactions on Neural Networks and Learning Systems</a> </i> &nbsp;
Based on this general model, sparse kernel embedding is also proposed for nonlinear sparse feature extraction.  ...  The optimal sparse embeddings derived from the proposed framework can be computed by iterating the modified elastic net and singular value decomposition.  ...  embedding (SKE) perform better than the classical sparse subspace learning methods, the sparse, and nonsparse manifold learning-based algorithms in feature extraction and classification.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tnnls.2015.2422994">doi:10.1109/tnnls.2015.2422994</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/25955995">pmid:25955995</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mfi7hm7hgbfrpo62p53niahm4u">fatcat:mfi7hm7hgbfrpo62p53niahm4u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20160429143559/http://yongxu.org/paper/Approximate%20orthogonal%20sparse%20embedding%20for%20dimensionality%20reduction%20OK.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ed/0a/ed0a761386436dcd614a0fc8f1e7a2eff9c45327.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tnnls.2015.2422994"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

A review on distance based time series classification

Amaia Abanda, Usue Mori, Jose A. Lozano
<span title="2018-11-01">2018</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ja54f4dcmzfz7cvlo7o757jdba" style="color: black;">Data mining and knowledge discovery</a> </i> &nbsp;
In other cases, the distances are employed to obtain a time series kernel and enable the use of kernel methods for time series classification.  ...  The particularity of the data makes it a challenging task and different approaches have been taken, including the distance based approach. 1-NN has been a widely used method within distance based time  ...  Another feature based method consists of embedding.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10618-018-0596-4">doi:10.1007/s10618-018-0596-4</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/t57qk2xy5vfutj6scb5zc2fnoa">fatcat:t57qk2xy5vfutj6scb5zc2fnoa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200508024443/https://bird.bcamath.org/bitstream/handle/20.500.11824/888/review.pdf;jsessionid=4BA131BCCA0D117FC29BF9CEF76DA0C9?sequence=1" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/56/28/562821c3404b1536fb19adeb229390bf38b4408e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10618-018-0596-4"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Multivariate pattern analysis strategies in detection of remitted major depressive disorder using resting state functional connectivity

Runa Bhaumik, Lisanne M. Jenkins, Jennifer R. Gowins, Rachel H. Jacobs, Alyssa Barba, Dulal K. Bhaumik, Scott A. Langenecker
<span title="">2017</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/47gmsc3hojdm5kdlgbg4peyvyi" style="color: black;">NeuroImage: Clinical</a> </i> &nbsp;
We empirically evaluated four feature selection methods including multivariate Least Absolute Shrinkage and Selection Operator (LASSO) and Elastic Net feature selection algorithms.  ...  Our results showed that SVM classification with Elastic Net feature selection achieved the highest classification accuracy of 76.1% (sensitivity of 81.5% and specificity of 68.9%) by leaveone-out cross-validation  ...  In contrast, the embedded methods LASSO and Elastic Net algorithms discard the unimportant features by forcing them to zero, so there is no ranking of features.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.nicl.2016.02.018">doi:10.1016/j.nicl.2016.02.018</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/28861340">pmid:28861340</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5570580/">pmcid:PMC5570580</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/n6y3o4sykbg4bm2l2lypfstxfa">fatcat:n6y3o4sykbg4bm2l2lypfstxfa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200211170820/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC5570580&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f8/72/f8722e5c3cc9708fb4b21d06aa7ad062bb9c7b34.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.nicl.2016.02.018"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> elsevier.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5570580" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Quantifying performance of machine learning methods for neuroimaging data

Lee Jollans, Rory Boyle, Eric Artiges, Tobias Banaschewski, Sylvane Desrivières, Antoine Grigis, Jean-Luc Martinot, Tomáš Paus, Michael N. Smolka, Henrik Walter, Gunter Schumann, Hugh Garavan (+1 others)
<span title="2019-06-05">2019</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/sa477uo7lveh7hchpikpixop5u" style="color: black;">NeuroImage</a> </i> &nbsp;
Five machine learning regression methods - Gaussian Process Regression, Multiple Kernel Learning, Kernel Ridge Regression, the Elastic Net and Random Forest, were examined with both real and simulated  ...  When the effect size was large, the Elastic Net, Kernel Ridge Regression and Gaussian Process Regression performed well at most sample sizes and feature set sizes.  ...  RF: Random Forest; MR: Multiple Regression; EN: Elastic Net; MKL: Multiple Kernel Learning; KRR: Kernel Ridge Regression; GPR: Gaussian Process Regression.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.neuroimage.2019.05.082">doi:10.1016/j.neuroimage.2019.05.082</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/31173905">pmid:31173905</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6688909/">pmcid:PMC6688909</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ho7alg2l7fepljrvblmngl6nxq">fatcat:ho7alg2l7fepljrvblmngl6nxq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220125205822/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC6688909&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/34/e5/34e534a6d324e5e4a70d7daf7ffa252a58c78278.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.neuroimage.2019.05.082"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> elsevier.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6688909" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Discrete Elastic Inner Vector Spaces with Application to Time Series and Sequence Mining

Pierre-Francois Marteau, Nicolas Bonnel, Gildas Menier
<span title="">2013</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ht3yl6qfebhwrg7vrxkz4gxv3q" style="color: black;">IEEE Transactions on Knowledge and Data Engineering</a> </i> &nbsp;
This framework is based on a recursive definition that covers the case of multiple embedded time elastic dimensions.  ...  Classification experimentations on time series and symbolic sequences datasets demonstrate the benefits that we can expect by embedding time series or sequences into elastic inner spaces rather than into  ...  Indexing for fast retrieval in time series data bases Prop.2.3 shows how the elastic inner product generalizes the Euclidean inner product when time series are embedded into a finite dimensional vector  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tkde.2012.131">doi:10.1109/tkde.2012.131</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xdvu7ssf4jhonfnru5ermakali">fatcat:xdvu7ssf4jhonfnru5ermakali</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20140830112305/http://hal.inria.fr/docs/00/71/23/10/PDF/ElasticVectorSpaceFinalSub.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/6c/c4/6cc4f3b7885867fd8b7a0de80b1f19981a8dd2b1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tkde.2012.131"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>
&laquo; Previous Showing results 1 &mdash; 15 out of 3,399 results