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Comprehensive Review On Twin Support Vector Machines [article]

M. Tanveer and T. Rajani and R. Rastogi and Y.H. Shao and M. A. Ganaie
<span title="2021-11-06">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Twin support vector machine (TWSVM) and twin support vector regression (TSVR) are newly emerging efficient machine learning techniques which offer promising solutions for classification and regression  ...  It requires to solve two small sized quadratic programming problems (QPPs) in lieu of solving single large size QPP in support vector machine (SVM) while TSVR is formulated on the lines of TWSVM and requires  ...  Research progress on Twin Support Vector Regression In this section, we discuss the progress of twin SVM based models for the regression problems.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2105.00336v2">arXiv:2105.00336v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/prxup4sbavfyxpembij6amrnka">fatcat:prxup4sbavfyxpembij6amrnka</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211120123115/https://arxiv.org/pdf/2105.00336v2.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/aa/55/aa55b93defae3ad124dce29619cc045a68a19c56.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2105.00336v2" 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>

Linear Maximum Margin Classifier for Learning from Uncertain Data

Christos Tzelepis, Vasileios Mezaris, Ioannis Patras
<span title="">2017</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3px634ph3vhrtmtuip6xznraqi" style="color: black;">IEEE Transactions on Pattern Analysis and Machine Intelligence</a> </i> &nbsp;
More specifically, we reformulate the SVM framework such that each training example can be modeled by a multi-dimensional Gaussian distribution described by its mean vector and its covariance matrix --  ...  The resulting classifier, which we name SVM with Gaussian Sample Uncertainty (SVM-GSU), is tested on synthetic data and five publicly available and popular datasets; namely, the MNIST, WDBC, DEAP, TV News  ...  In [27] , motivated by GEPSVM [28] , Qi et al. robustified a twin support vector machine (TWSVM) [29] . Robust TWSVM [27] deals with data affected by measurement noise using a SOCP formulation.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tpami.2017.2772235">doi:10.1109/tpami.2017.2772235</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/29990153">pmid:29990153</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6snjmdesgnacrioo5lqpi3vx6i">fatcat:6snjmdesgnacrioo5lqpi3vx6i</a> </span>
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Robust Detection of Covariate-Treatment Interactions in Clinical Trials [article]

Baptiste Goujaud, Eric W. Tramel, Pierre Courtiol, Mikhail Zaslavskiy, Gilles Wainrib
<span title="2017-12-21">2017</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We propose a set of novel univariate statistical tests, based on the theory of random walks, which are able to capture non-linear and non-monotonic covariate-treatment interactions.  ...  The increasing volume of data accumulated in clinical trials provides a unique opportunity to discover new biomarkers and further the goal of personalized medicine, but it also requires innovative robust  ...  In [12] , [13] , SIDES method based differential effect search [14] , virtual twins method [15] , subgroup analysis via recursive partitioning, combined additive and tree based regression [16] and  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1712.08211v1">arXiv:1712.08211v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6o4wze4bjjfftjmctqllfehyrq">fatcat:6o4wze4bjjfftjmctqllfehyrq</a> </span>
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Calcite Twin Formation, Measurement and Use as Stress–Strain Indicators: A Review of Progress over the Last Decade

Olivier Lacombe, Camille Parlangeau, Nicolas E. Beaudoin, Khalid Amrouch
<span title="">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/f7pwyorpnrco3p6jydb45t4hf4" style="color: black;">Geosciences</a> </i> &nbsp;
This review summarises the recent progress in the understanding of twin formation, including nucleation and growth of twins, and discusses the concept of CRSS and its dependence on several factors such  ...  This review also presents how the age of twinning events in natural rocks can be constrained while individual twins cannot be dated yet.  ...  This supports the dependence of twinning occurrence and CRSS on grain size.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/geosciences11110445">doi:10.3390/geosciences11110445</a> <a target="_blank" rel="external noopener" href="https://doaj.org/article/72542d78c985465aa9865ee96a3dbf5c">doaj:72542d78c985465aa9865ee96a3dbf5c</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6tdneuvi6fhyfjt3spay26oszq">fatcat:6tdneuvi6fhyfjt3spay26oszq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220312090039/https://mdpi-res.com/d_attachment/geosciences/geosciences-11-00445/article_deploy/geosciences-11-00445.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/44/f2/44f28d3eaaee86ae0ecda4dd372a431b71d1b9e1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/geosciences11110445"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Master's Thesis : Deep Learning for Visual Recognition [article]

Rémi Cadène, Nicolas Thome, Matthieu Cord
<span title="2016-10-18">2016</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Our last contribution is a framework, build on top of Torch7, for training and testing deep models on any visual recognition tasks and on datasets of any scale.  ...  The originality of our work lies in our approach focusing on tasks with a low amount of data.  ...  Lastly, I thank my family and friends for their love and support.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1610.05567v1">arXiv:1610.05567v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/hdgwemcxrrhgxmesddanftmtba">fatcat:hdgwemcxrrhgxmesddanftmtba</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191024073227/https://arxiv.org/pdf/1610.05567v1.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/74/cf74dceae075bde213d2aafad115d2afc893c21b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1610.05567v1" 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>

The External Balance Assessment Methodology: 2018 Update

Luis Cubeddu, Signe Krogstrup, Gustavo Adler, Pau Rabanal, Mai Chi Dao, Swarnali Ahmed Hannan, Luciana Juvenal, Carolina Osorio Buitron, Cyril Rebillard, Daniel Garcia-Macia, Callum Jones, Jair Rodriguez (+4 others)
<span title="">2019</span> <i title="International Monetary Fund (IMF)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/u2exkadp6bg6nn24edo5uhacpq" style="color: black;">IMF Working Papers</a> </i> &nbsp;
2002) WGI from 2002; base pre 2002 on ICRG/WGI relation Table 4 . 4 EBA Current Account Regression Results, Robustness on Credit Baseline Higher Lambda Demeaned Credit -to- GDP Demeaned  ...  on future generations for old-age support.  ...  This variable enters directly (not relative) in level terms and is also interacted with a dummy that takes on the value of one if the NFA position is below negative 60 percent of GDP.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5089/9781498300933.001">doi:10.5089/9781498300933.001</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yfef3jdjdrgkdmwvj442am5q6a">fatcat:yfef3jdjdrgkdmwvj442am5q6a</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190428115730/https://www.elibrary.imf.org/doc/IMF001/25828-9781498300933/25828-9781498300933/Other_formats/Source_PDF/25828-9781498304658.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/0d/d5/0dd551c00740f0355708b42dd0c23122d63d689f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5089/9781498300933.001"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Monitoring & Controlling of Information against Unethical Hacking using Effective Machine Learning Techniques

<span title="2020-06-30">2020</span> <i title="Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/h673cvfolnhl3mnbjxkhtxdtg4" style="color: black;">International Journal of Engineering and Advanced Technology</a> </i> &nbsp;
At the moment, deal with the concern of ill-disposed AI; i.e., our experts will most likely generate risk-free AI calculations robust within the attraction of a loud or an adversely managed information  ...  Determining the proper selection unequivocally relies on the rightness of the relevant information.  ...  The objective is a soft approximation of a convex component (the prepared for hinge-loss).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35940/ijeat.e9928.069520">doi:10.35940/ijeat.e9928.069520</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/l5duyhhea5dzbhtjakjrjblshm">fatcat:l5duyhhea5dzbhtjakjrjblshm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200711112029/https://www.ijeat.org/wp-content/uploads/papers/v9i5/E9928069520.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/ac/19/ac19327eea14d2c20d7c8639786ac44dea3eeae1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35940/ijeat.e9928.069520"> <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>

An Efficient and Accurate Iris Recognition Algorithm Based on a Novel Condensed 2-ch Deep Convolutional Neural Network

Guoyang Liu, Weidong Zhou, Lan Tian, Wei Liu, Yingjian Liu, Hanwen Xu
<span title="2021-05-27">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
Moreover, the gradient-based analysis results indicate that the proposed algorithm is robust to various image contaminations.  ...  This work focuses on training a novel condensed 2-channel (2-ch) CNN with few training samples for efficient and accurate iris identification and verification.  ...  Acknowledgments: We gratefully acknowledge the support from the above funds. Conflicts of Interest: The authors declare no conflict of interest.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21113721">doi:10.3390/s21113721</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34071850">pmid:34071850</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wtboadxr6jgd7gjcl3idkj3dyq">fatcat:wtboadxr6jgd7gjcl3idkj3dyq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210603090840/https://res.mdpi.com/d_attachment/sensors/sensors-21-03721/article_deploy/sensors-21-03721.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/5a/03/5a03455627f848e9ee0ee2aa68832ff2421612b6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21113721"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Human-in-the-Loop Methods for Data-Driven and Reinforcement Learning Systems [article]

Vinicius G. Goecks
<span title="2020-08-30">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Results presented in this work show that the reward signal that is learned based upon human interaction accelerates the rate of learning of reinforcement learning algorithms and that learning from a combination  ...  Common cost function for classification are Cross-Entropy and Hinge loss while for regression we have Mean Squared Error L CE (y i ,ŷ i ) = − 1 N N i C j=1 y ij log(ŷ ij ), is used for classification  ...  Binary Cross-Entropy (BCE) loss, also known as Log loss, is the special case of the CE loss when the number of classes C is equal to 2 (binary classification problem) and is written as Hinge loss, often  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2008.13221v1">arXiv:2008.13221v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/aofoenmwcvckvagbttrkskevty">fatcat:aofoenmwcvckvagbttrkskevty</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200903024331/https://arxiv.org/pdf/2008.13221v1.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] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2008.13221v1" 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>

Gene‐Environment Effects on Female Fertility

Nicola Barban, Libertad González, Marco Francesconi, DuEPublico: Duisburg-Essen Publications Online, University Of Duisburg-Essen
<span title="2021-10-18">2021</span> <i > <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/bl526pmvyjds7c2drei6ziv4ri" style="color: black;">CINCH working paper series</a> </i> &nbsp;
Both genes and environment exert substantial influences on all outcomes.  ...  on twins data (Tropf et al., 2017) .  ...  on twins or siblings data has been constrained to.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.17185/duepublico/74910">doi:10.17185/duepublico/74910</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ze2tbwnzf5edpl6l3bcoxq2fiq">fatcat:ze2tbwnzf5edpl6l3bcoxq2fiq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211101095109/https://duepublico2.uni-due.de/servlets/MCRFileNodeServlet/duepublico_derivate_00074642/CINCH_WP_2021_07.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/60/9d/609d7b3df951c510201b231aba4cbf1a337572b2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.17185/duepublico/74910"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Modern applications of machine learning in quantum sciences [article]

Anna Dawid, Julian Arnold, Borja Requena, Alexander Gresch, Marcin Płodzień, Kaelan Donatella, Kim Nicoli, Paolo Stornati, Rouven Koch, Miriam Büttner, Robert Okuła, Gorka Muñoz-Gil (+17 others)
<span title="2022-04-08">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
, while SVMs uses a function called the Hinge loss.  ...  Support vector machines In the previous section, we have discussed how to use kernel methods for regression problems (in particular ridge regression).  ...  A Mathematical details on principal component analysis We can motivate PCA from two different perspectives: The first one is sketched in the main text and is based on retaining the largest possible data  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2204.04198v1">arXiv:2204.04198v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rae77aetd5hahnovchru6kjbcy">fatcat:rae77aetd5hahnovchru6kjbcy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220411054835/https://arxiv.org/ftp/arxiv/papers/2204/2204.04198.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/d7/1e/d71e799a4dd80d71be0f52fa3b8060a5f6de956b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2204.04198v1" 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>

Pretrained Transformers for Text Ranking: BERT and Beyond

Andrew Yates, Rodrigo Nogueira, Jimmy Lin
<span title="2021-03-08">2021</span> <i title="ACM"> Proceedings of the 14th ACM International Conference on Web Search and Data Mining </i> &nbsp;
We'd like to thank the following people for comments on earlier drafts of this work: Maura Grossman, Sebastian Hofstätter, Xueguang Ma, and Bhaskar Mitra.  ...  Acknowledgements 129 Acknowledgements This research was supported in part by the Canada First Research Excellence Fund and the Natural Sciences and Engineering Research Council (NSERC) of Canada.  ...  The model is trained with a negative log likelihood loss rather than the pairwise hinge loss used by RepBERT.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/3437963.3441667">doi:10.1145/3437963.3441667</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6teqmlndtrgfvk5mneq5l7ecvq">fatcat:6teqmlndtrgfvk5mneq5l7ecvq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210716210049/https://pure.mpg.de/rest/items/item_3287344_1/component/file_3287345/content" 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/6f/1f/6f1fdd10b2db028d7695d3b3c9748f030b201888.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/3437963.3441667"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Simulated Non-Parametric Estimation of Dynamic Models

FILIPPO ALTISSIMO, ANTONIO MELE
<span title="">2009</span> <i title="Oxford University Press (OUP)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4gp7xsp5mndehl3evvt3ibyvbi" style="color: black;">The Review of Economic Studies</a> </i> &nbsp;
Perhaps one of the best known approaches hinges on the goodness-of-fit tests initiated by Bickel and Rosenblatt (1973) .  ...  Even with integration quadratures, one can still reduce the computational burden, with a loss in efficiency.  ...  Remarks on Assumption 10(b).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1111/j.1467-937x.2008.00527.x">doi:10.1111/j.1467-937x.2008.00527.x</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yc7uwtnvrze2bgzadz44wlbtpi">fatcat:yc7uwtnvrze2bgzadz44wlbtpi</a> </span>
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Controlling Recurrent Neural Networks by Conceptors [article]

Herbert Jaeger
<span title="2017-04-22">2017</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
abstract, focus, morph, generalize, de-noise and recognize a large number of dynamical patterns within a single neural system; novel patterns can be added without interfering with previously acquired ones  ...  from 5 – 12 test misclassifications, all using specialized versions of temporal support vector machines).  ...  four equidistant support points.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1403.3369v3">arXiv:1403.3369v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4gaiy3cikvervdjvsmp47b2byy">fatcat:4gaiy3cikvervdjvsmp47b2byy</a> </span>
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CARS 2020—Computer Assisted Radiology and Surgery Proceedings of the 34th International Congress and Exhibition, Munich, Germany, June 23–27, 2020

<span title="">2020</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ohr6juw5xrcrzgnsati6eq3edq" style="color: black;">International Journal of Computer Assisted Radiology and Surgery</a> </i> &nbsp;
With an increasing general demand and pressure on CARS to also go fully digital in the long term, many members of the CARS Congress Organizing Committee, however, are more cautious and convinced that one  ...  Aiming to stimulate complimentary thoughts and actions on what is being presented at CARS, implies a number of enabling variables for optimal analogue scholarly communication, such as (examples given are  ...  The work is supported by a grant-in-aid for scientific research on innovative areas, JSPS KAKENHI 17K17680. We thank Coordination for the Improvement of Higher Education Personnel (CAPES).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s11548-020-02171-6">doi:10.1007/s11548-020-02171-6</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32514840">pmid:32514840</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lyhdb2zfpjcqbf4mmbunddwroq">fatcat:lyhdb2zfpjcqbf4mmbunddwroq</a> </span>
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