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Global Sparse Analysis Framework

Hakjoo Oh, Kihong Heo, Wonchan Lee, Woosuk Lee, Daejun Park, Jeehoon Kang, Kwangkeun Yi
<span title="2014-09-25">2014</span> <i title="Association for Computing Machinery (ACM)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4hplau6wtnhnfnqt2t7vbri6vm" style="color: black;">ACM Transactions on Programming Languages and Systems</a> </i> &nbsp;
Analysis designers first use the abstract interpretation framework to have a global and correct static analyzer whose scalability is unattended.  ...  We formally present our framework; we present that existing sparse analyses are all restricted instances of our framework; we show more semantically elaborate design examples of sparse non-relational and  ...  Sparse Analysis Framework In this section, we develop our sparse analysis framework.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/2590811">doi:10.1145/2590811</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fyrg6owbtbbixhaoycmti75s5q">fatcat:fyrg6owbtbbixhaoycmti75s5q</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170810164623/http://rosaec.snu.ac.kr/publish/2013/techmemo/ROSAEC-2013-014.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/9d/68/9d682a2304de2a53ff20ffecf3802f4a8e1a999d.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/2590811"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

A general framework for the design and analysis of sparse FIR linear equalizers

Abubakr O. Al-Abbasi, Ridha Hamila, Waheed U. Bajwa, Naofal Al-Dhahir
<span title="">2015</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/qt5pvjrtkjfdzgqcdlcw2blce4" style="color: black;">2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP)</a> </i> &nbsp;
Finally, the usefulness of the proposed framework for the design of sparse FIR LEs is validated through numerical experiments.  ...  In this paper, a general framework is provided that transforms the problem of sparse linear equalizers (LEs) design into the problem of sparsest-approximation of a vector in different dictionaries.  ...   ∆ = − * ∆ , Proposed sparse approximation framework  We provide a general framework for designing sparse FIR LEs and equalizers that can be considered as the problem of sparse approximation using  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/globalsip.2015.7418314">doi:10.1109/globalsip.2015.7418314</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/globalsip/Al-AbbasiHBA15.html">dblp:conf/globalsip/Al-AbbasiHBA15</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/scarafjswjfxrjxbazvfv6vzhe">fatcat:scarafjswjfxrjxbazvfv6vzhe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200709120928/https://sigport.org/sites/default/files/Pres-Dec_GlobalSIP2015.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/9e/80/9e802a1ddee320f4ec35ef9a7d5145961a438071.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/globalsip.2015.7418314"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Design and implementation of sparse global analyses for C-like languages

Hakjoo Oh, Kihong Heo, Wonchan Lee, Woosuk Lee, Kwangkeun Yi
<span title="2012-06-11">2012</span> <i title="Association for Computing Machinery (ACM)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xu5bk2lj5rbdxlx6222nw7tsxi" style="color: black;">SIGPLAN notices</a> </i> &nbsp;
We first use the abstract interpretation framework to have a global static analyzer whose scalability is unattended.  ...  Our method generalizes the sparse analysis techniques on top of the abstract interpretation framework to support relational as well as non-relational semantics properties for C-like languages.  ...  Our framework bridges the gap between the two existing technologies -abstract interpretation and sparse analysis -towards the design of sound, yet scalable global static analyzers.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/2345156.2254092">doi:10.1145/2345156.2254092</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rwvxvu2uefdi3e4igt5u6gyxim">fatcat:rwvxvu2uefdi3e4igt5u6gyxim</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20120425061119/http://ropas.snu.ac.kr:80/~wclee/papers/pldi12b.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/e7/f8/e7f87f3b5ee847061728595c01fea5303767c74b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/2345156.2254092"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Design and implementation of sparse global analyses for C-like languages

Hakjoo Oh, Kihong Heo, Wonchan Lee, Woosuk Lee, Kwangkeun Yi
<span title="">2012</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jpubwsjaozha5itdes6pzyz2fm" style="color: black;">Proceedings of the 33rd ACM SIGPLAN conference on Programming Language Design and Implementation - PLDI &#39;12</a> </i> &nbsp;
We first use the abstract interpretation framework to have a global static analyzer whose scalability is unattended.  ...  Our method generalizes the sparse analysis techniques on top of the abstract interpretation framework to support relational as well as non-relational semantics properties for C-like languages.  ...  Section 2 explains our sparse analysis framework. Section 3 and 4 design sparse non-relational and relational analysis, respectively, based on our framework.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/2254064.2254092">doi:10.1145/2254064.2254092</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/pldi/OhHLLY12.html">dblp:conf/pldi/OhHLLY12</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fjfts2aodzekreektd6oofje7m">fatcat:fjfts2aodzekreektd6oofje7m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20130404075607/http://rosaec.snu.ac.kr/publish/2012/T1/OhHeLeLeYi-PLDI-2012.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/cf/e0/cfe0bc5a0b94123f5c0564493ab6f34dfd295a92.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/2254064.2254092"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Modular Weighted Global Sparse Representation for Robust Face Recognition

Jian Lai, Xudong Jiang
<span title="">2012</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/msfmoh6v7bdk7lrsmtbklto74i" style="color: black;">IEEE Signal Processing Letters</a> </i> &nbsp;
The proposed framework advances both the modular and global sparse representation approaches, especially in dealing with disguise, large illumination variations and expression changes.  ...  This work proposes a novel framework of robust face recognition based on the sparse representation.  ...  Many methods have been proposed to solve this problem, such as Principle Component Analysis (PCA) [1] , Linear Discriminant Analysis (LDA) [2] , Independent Component Analysis (ICA) [3] , Eigenfeature  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/lsp.2012.2207112">doi:10.1109/lsp.2012.2207112</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/batysbdxnffchngf7ggkmginku">fatcat:batysbdxnffchngf7ggkmginku</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170829142058/http://www3.ntu.edu.sg/home/EXDJiang/JiangX.D.-SPL-12.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/67/e0/67e0acfc9d5fc8184a29c9d94fe010551c47d817.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/lsp.2012.2207112"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

A Unified Point-Based Framework for 3D Segmentation [article]

Hung-Yueh Chiang, Yen-Liang Lin, Yueh-Cheng Liu, Winston H. Hsu
<span title="2019-08-18">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We present a new unified point-based framework for 3D point cloud segmentation that effectively optimizes pixel-level features, geometrical structures and global context priors of an entire scene.  ...  In addition, we investigate a global context prior to obtain a better prediction.  ...  Feature Analysis We evaluate different types of features in our unified framework: 3D coordinates (xyz), vertex normal (n), global context (gc) and 2D image features (d), as shown in Table 3 .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1908.00478v4">arXiv:1908.00478v4</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/azt6qrdjzragdpfeotysaufhsu">fatcat:azt6qrdjzragdpfeotysaufhsu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200930000708/https://arxiv.org/pdf/1908.00478v3.pdf" title="fulltext PDF download [not primary version]" 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] <span style="color: #f43e3e;">&#10033;</span> <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ca/e6/cae6494f0f698b175e474ee2b47fc7ce20916e7c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1908.00478v4" 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>

Transform learning MRI with global wavelet regularization

A. Korhan Tanc, Ender M. Eksioglu
<span title="">2015</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wiu3vyiu4fcgnd4znybulgkh6m" style="color: black;">2015 23rd European Signal Processing Conference (EUSIPCO)</a> </i> &nbsp;
In this work we jointly enforce a global wavelet domain sparsity constraint together with a patch level, learned analysis sparsity prior.  ...  Recently, new methods have been proposed which perform sparse regularization on patches extracted from the image.  ...  TRANSFORM LEARNING MRI FORMULATION TL framework for analysis sparse representation has been introduced in [7] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/eusipco.2015.7362705">doi:10.1109/eusipco.2015.7362705</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/eusipco/TancE15.html">dblp:conf/eusipco/TancE15</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pev5epnwpbattbimmcamydqgpq">fatcat:pev5epnwpbattbimmcamydqgpq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170808111131/http://web.itu.edu.tr/eksioglue/preprints/eusipco_mri_conference.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/80/7b/807bbb0ce50b39a19197e7f0289fe5ba6a2ce215.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/eusipco.2015.7362705"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Image denoising through multi-scale learnt dictionaries

Jeremias Sulam, Boaz Ophir, Michael Elad
<span title="">2014</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/anlh4tvwprcrtoxv5d4h6a7rye" style="color: black;">2014 IEEE International Conference on Image Processing (ICIP)</a> </i> &nbsp;
In this paper we present a patch-based denoising algorithm relying on a sparsity-inspired model (K-SVD), which uses a multi-scale analysis framework.  ...  We then combine the single scale and multi-scale approaches by merging both outputs by weighted joint sparse coding of the images.  ...  RELATED WORK The idea of combining dictionary learning with a multi-scale analysis framework is not new.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icip.2014.7025162">doi:10.1109/icip.2014.7025162</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icip/SulamOE14.html">dblp:conf/icip/SulamOE14</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/d3ryr4jmoncdlfrie7rl4ibm6y">fatcat:d3ryr4jmoncdlfrie7rl4ibm6y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170809120512/http://www.cs.technion.ac.il/~elad/publications/conferences/2014/ICIP-2014-MultiScaleDicLearning.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/f7/81/f7817f0af1f0f59918c8ce77a4d2af198eb7c539.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icip.2014.7025162"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Non-rigid 3D Shape Retrieval via Sparse Representation [article]

Lili Wan, Shuai Li, Zhenjiang J. Miao, Yigang G. Cen
<span title="">2013</span> <i title="The Eurographics Association"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/b7jv7gwrbfg6ja4cdhjozcc6sa" style="color: black;">Pacific Conference on Computer Graphics and Applications</a> </i> &nbsp;
In this paper, we present a new method to pool the local shape descriptors into a global shape descriptor by means of sparse representation.  ...  Finally, the HKSs of each 3D model are sparsely coded based on the learned dictionary, and such sparse representations can be further integrated to form an object-level shape descriptor.  ...  Based on this theory, we propose a framework to extract a global shape descriptor, which is called Sparse Representation of HKS (SC HKS ).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2312/pe.pg.pg2013short.011-016">doi:10.2312/pe.pg.pg2013short.011-016</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/pg/WanLMC13.html">dblp:conf/pg/WanLMC13</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ipmzkhrln5frtlgv74vvvoy6bq">fatcat:ipmzkhrln5frtlgv74vvvoy6bq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220119234229/https://diglib.eg.org/xmlui/bitstream/handle/10.2312/PE.PG.PG2013short.011-016/011-016.pdf;jsessionid=3A18B6D513C6ABDC4B764DEDDB2C48EA?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/71/5f/715f83bab38852185f7d07c6816422df3265c049.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2312/pe.pg.pg2013short.011-016"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Sparse and noisy LiDAR completion with RGB guidance and uncertainty [article]

Wouter Van Gansbeke, Davy Neven, Bert De Brabandere, Luc Van Gool
<span title="2019-02-14">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We propose a new framework which extracts both global and local information in order to produce proper depth maps. We argue that simple depth completion does not require a deep network.  ...  This work proposes a new method to accurately complete sparse LiDAR maps guided by RGB images.  ...  Using the sparse input and the semi-sparse ground truth, the convolutional framework makes use of global guidance information to correct artifacts and to upsample the input properly.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1902.05356v1">arXiv:1902.05356v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zsrrqu2mujfbrbe4rywpvasov4">fatcat:zsrrqu2mujfbrbe4rywpvasov4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191027102505/https://arxiv.org/pdf/1902.05356v1.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/f9/75/f9755ebb6c9a1249b1543d58e5f334743f7351de.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1902.05356v1" 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>

Multi-scale mesh saliency based on low-rank and sparse analysis in shape feature space

Shengfa Wang, Nannan Li, Shuai Li, Zhongxuan Luo, Zhixun Su, Hong Qin
<span title="">2015</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/d7m3pqsgunbsrmcxdnyqqx2uxm" style="color: black;">Computer Aided Geometric Design</a> </i> &nbsp;
By focusing on the sparse components, we develop a versatile, structure-sensitive saliency detection framework, which can distinguish local geometry saliency and global structure saliency in various 3D  ...  This paper advocates a novel multi-scale mesh saliency method using the powerful lowrank and sparse analysis in shape feature space.  ...  To handle the aforementioned problems, we propose a versatile saliency detection framework based on the low-rank and sparse analysis, as shown in Fig. 1 .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.cagd.2015.03.003">doi:10.1016/j.cagd.2015.03.003</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fc3ltb2x7vboxdnt2tiujogwvi">fatcat:fc3ltb2x7vboxdnt2tiujogwvi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20160610100453/http://www3.cs.stonybrook.edu/~qin/research/2015-cagd-multi-scale-mesh-saliency.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/3b/2b/3b2b55b9980ad6c256aa73502dc15e928deeed53.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.cagd.2015.03.003"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

A Framework to Compare Tractography Algorithms Based on Their Performance in Predicting Functional Networks [chapter]

Fani Deligianni, Chris A. Clark, Jonathan D. Clayden
<span title="">2013</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
We use a model selection framework based on sparse canonical correlation analysis and an appropriate metric to evaluate the similarity between the predicted and the observed functional networks.  ...  Here, we build a statistical framework to compare the performance of local and global tractograpy in predicting functional brain networks.  ...  To this end, we have developed a predictive framework based on sparse canonical correlation analysis (SCCA) [6] . SCCA is a special case of sparse reduced rank regression [7] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-02126-3_21">doi:10.1007/978-3-319-02126-3_21</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/z3puwni26va5jl5q6cr4mya7ai">fatcat:z3puwni26va5jl5q6cr4mya7ai</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20160417222956/http://www.homepages.ucl.ac.uk:80/~ucbtfde/pdfs/mypubs/mbia13.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/32/26/3226f15393000a7d0720bb14a4f9824d1e5aa8bf.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-02126-3_21"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Deep Convex Representations: Feature Representations for Bioacoustics Classification

Anshul Thakur, Vinayak Abrol, Pulkit Sharma, Padmanabhan Rajan
<span title="2018-09-02">2018</span> <i title="ISCA"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/trpytsxgozamtbp7emuvz2ypra" style="color: black;">Interspeech 2018</a> </i> &nbsp;
Archetypal analysis, a form of convex non-negative matrix factorization, is used for acoustic modelling at each level of this framework.  ...  In this paper, a deep convex matrix factorization framework is proposed for bioacoustics classification.  ...  Archetypal analysis (AA) [11] form the crux of the proposed framework. AA decomposes a matrix X as: X ≈ DA, where D is a dictionary and A is convex-sparse representation.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.21437/interspeech.2018-1705">doi:10.21437/interspeech.2018-1705</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/interspeech/ThakurASR18.html">dblp:conf/interspeech/ThakurASR18</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wyivhzgglbh3lgejzz7b3kn7um">fatcat:wyivhzgglbh3lgejzz7b3kn7um</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190303155937/http://pdfs.semanticscholar.org/afd7/4a608f44321fcb36f40055f6cde3ada2b1ae.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/af/d7/afd74a608f44321fcb36f40055f6cde3ada2b1ae.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.21437/interspeech.2018-1705"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Integrated Registration, Segmentation, and Interpolation for 3D/4D Sparse Data

Adeline Paiement
<span title="2015-12-21">2015</span> <i title="Universitat Autonoma de Barcelona"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tacfpjxccve3bmtvwxtrw3krn4" style="color: black;">ELCVIA Electronic Letters on Computer Vision and Image Analysis</a> </i> &nbsp;
The analysis of such tomographic data is essential for establishing a diagnosis or planning surgery.  ...  We address the problem of object modelling from 3D and 4D sparse data acquired as different sequences which are misaligned with respect to each other.  ...  We propose a new method to integrate these stages in a level set framework.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5565/rev/elcvia.712">doi:10.5565/rev/elcvia.712</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vra34rhfkfbopekvdagl3ohrea">fatcat:vra34rhfkfbopekvdagl3ohrea</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170812171501/http://ddd.uab.cat/pub/elcvia/elcvia_a2015v14n3/elcvia_a2015v14n3p6.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/d1/6f/d16fd385482f2db2867ab55d619b4402d546bf2d.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5565/rev/elcvia.712"> <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>

Sparse Optimization for Motion Segmentation [chapter]

Michael Ying Yang, Sitong Feng, Bodo Rosenhahn
<span title="">2015</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
To the best of our knowledge, our framework is the first one to apply the sparse optimization for optimizing the global and local subspace simultaneously.  ...  applies the sparse PCA (SPCA) to obtain a projected subspace, which is a low-dimensional global subspace on a Stiefel manifold with sparse entries.  ...  Sparse Optimization for Motion Segmentation  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-16631-5_28">doi:10.1007/978-3-319-16631-5_28</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/46pelypkbjgnbozok2gn2wejoa">fatcat:46pelypkbjgnbozok2gn2wejoa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170829164234/http://vigir.missouri.edu/~gdesouza/Research/Conference_CDs/ACCV_2014/pages/workshop10/pdffiles/w10-p4.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/27/d0/27d027b2374c9858b5dcecbb8b26d3e36cdf66f7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-16631-5_28"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>
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