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On the construction of extreme learning machine for online and offline one-class classification—An expanded toolbox

Chandan Gautam, Aruna Tiwari, Qian Leng
<span title="">2017</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/bby322qx6ndsje4ypr56c7nnly" style="color: black;">Neurocomputing</a> </i> &nbsp;
Through proposed one-class classifiers, we intend to expand the functionality of the most used toolbox for OCC i.e. DD toolbox.  ...  In this paper, we present six OCC methods based on extreme learning machine (ELM) and Online Sequential ELM (OSELM).  ...  We propose an expansion of DD toolbox for both online and offline OCC based on ELM and OSELM.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.neucom.2016.04.070">doi:10.1016/j.neucom.2016.04.070</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fm47jii7ofdandjcpvdex7gcqi">fatcat:fm47jii7ofdandjcpvdex7gcqi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200928021435/https://arxiv.org/ftp/arxiv/papers/1701/1701.04516.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/ab/10/ab1013b95431795fa3cfe96414058cb55fa91d06.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.neucom.2016.04.070"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Automated Classification of L/R Hand Movement EEG Signals using Advanced Feature Extraction and Machine Learning

Mohammad H., Aya Samaha, Khaled AlKamha
<span title="">2013</span> <i title="The Science and Information Organization"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2yzw5hsmlfa6bkafwsibbudu64" style="color: black;">International Journal of Advanced Computer Science and Applications</a> </i> &nbsp;
advanced feature extraction techniques and machine learning algorithms.  ...  The datasets were inputted into two machine-learning algorithms: Neural Networks (NNs) and Support Vector Machines (SVMs).  ...  ACKNOWLEDGMENT The authors would like to acknowledge the financial support received from Applied Science University that helped in accomplishing the work of this article.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14569/ijacsa.2013.040628">doi:10.14569/ijacsa.2013.040628</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/65ivvmztv5hlbflcrctmv6umeu">fatcat:65ivvmztv5hlbflcrctmv6umeu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180719052650/http://thesai.org/Downloads/Volume4No6/Paper_28-Automated_Classification_of_LR_Hand_Movement_EEG_Signals_using_Advanced_Feature_Extraction_and_Machine_Learning.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/2f/40/2f40f04fb5089f3cd77ea30120dfb5181dd82a37.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14569/ijacsa.2013.040628"> <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>

Online Learning with Regularized Kernel for One-class Classification [article]

Chandan Gautam, Aruna Tiwari, Sundaram Suresh, Kapil Ahuja
<span title="2018-04-09">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This paper presents an online learning with regularized kernel based one-class extreme learning machine (ELM) classifier and is referred as online RK-OC-ELM.  ...  The baseline kernel hyperplane model considers whole data in a single chunk with regularized ELM approach for offline learning in case of one-class classification (OCC).  ...  We would like to thank the editor and the anonymous reviewers that helped to greatly improve the quality of this manuscript.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1701.04508v2">arXiv:1701.04508v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/e327bwlstfcvpekl6qragnyp7y">fatcat:e327bwlstfcvpekl6qragnyp7y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200901161125/https://arxiv.org/pdf/1701.04508v2.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/83/50/83506159ea8e22badd5d96a16aea8d9b67ab6f1a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1701.04508v2" 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>

Towards unsupervised learning for automatic multi-class object detection in surveillance videos

Hasan Celik, Alan Hanjalic, Emile A. Hendriks
<span title="">2009</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rc5jnc4ldvhs3dswicq5wk3vsq" style="color: black;">2009 IEEE International Conference on Acoustics, Speech and Signal Processing</a> </i> &nbsp;
In our previous work we proposed an unsupervised method for learning and detecting the dominant object class in a general dynamic scene observed by a static camera.  ...  In this paper, we investigate the possibilities to expand the applicability of this method to the problem of multiple dominant object classes.  ...  Acknowledgments: The authors wish to thank Dr. Robert P.W. Duin for productive discussions and help with implementing the clustering module.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icassp.2009.4960385">doi:10.1109/icassp.2009.4960385</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icassp/CelikHH09.html">dblp:conf/icassp/CelikHH09</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/23y7nj4ck5d5fgw5bbg2ai4aiq">fatcat:23y7nj4ck5d5fgw5bbg2ai4aiq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170810085019/http://mirlab.org/conference_papers/International_Conference/ICASSP%202009/pdfs/0003521.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/52/6e/526e43bd2048d48857fc43f5e80c03208a396625.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icassp.2009.4960385"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Enhancing BCI-Based Emotion Recognition Using an Improved Particle Swarm Optimization for Feature Selection

Zina Li, Lina Qiu, Ruixin Li, Zhipeng He, Jun Xiao, Yan Liang, Fei Wang, Jiahui Pan
<span title="2020-05-27">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
To further validate the efficiency of the MLDW-PSO feature selection method, we developed an online two-class emotion recognition system evoked by Chinese videos, which achieved good performance for 10  ...  However, the current EEG-based emotion recognition has low accuracy of emotion classification, and its real-time application is limited.  ...  In addition, Zheng et.al [8] studied stable patterns of EEG over time for emotion recognition using a machine learning approach, and achieved a classification accuracy of 69.67%.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s20113028">doi:10.3390/s20113028</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32471047">pmid:32471047</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC7309000/">pmcid:PMC7309000</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qlftgo3ogbgxjankhgdldcaovu">fatcat:qlftgo3ogbgxjankhgdldcaovu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200529071420/https://res.mdpi.com/d_attachment/sensors/sensors-20-03028/article_deploy/sensors-20-03028.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/88/0d8820dbb47e7237159482e3e4ec977ba9158eeb.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s20113028"> <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> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309000" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Real-time neuroimaging and cognitive monitoring using wearable dry EEG

Tim R. Mullen, Christian A. E. Kothe, Yu Mike Chi, Alejandro Ojeda, Trevor Kerth, Scott Makeig, Tzyy-Ping Jung, Gert Cauwenberghs
<span title="">2015</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/nrcoa2vuhjcvfctty6zgus57um" style="color: black;">IEEE Transactions on Biomedical Engineering</a> </i> &nbsp;
Goal-We present and evaluate a wearable high-density dry electrode EEG system and an opensource software framework for online neuroimaging and state classification.  ...  The work addresses a need for robust real-time measurement and interpretation of complex brain activity in the dynamic environment of the wearable setting.  ...  The views and the conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tbme.2015.2481482">doi:10.1109/tbme.2015.2481482</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/26415149">pmid:26415149</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC4710679/">pmcid:PMC4710679</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ga7diwcisbdzladqgw2lq6beiq">fatcat:ga7diwcisbdzladqgw2lq6beiq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200429040742/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC4710679&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/ee/d7/eed72b8d3735ae567d474b8c087754fe43450079.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tbme.2015.2481482"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4710679" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Piece-wise Matching Layer in Representation Learning for ECG Classification [article]

Behzad Ghazanfari, Fatemeh Afghah, Sixian Zhang
<span title="2020-09-26">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We compared the performance of our method against a variety of known tuned methods from expert knowledge, machine learning, deep learning methods, and the combination of them.  ...  This paper proposes piece-wise matching layer as a novel layer in representation learning methods for electrocardiogram (ECG) classification.  ...  We acknowledge the support of NVIDIA Corporation with the donation of the Quadro P6000 used for this research.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2010.06510v1">arXiv:2010.06510v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/w3sommyu6rcmbf37ddpcdtqeh4">fatcat:w3sommyu6rcmbf37ddpcdtqeh4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201024075721/https://arxiv.org/pdf/2010.06510v1.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/6d/c6/6dc6b4e731180413ee395b421ebb3253f8ef397a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2010.06510v1" 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>

Context-aware mobile computing: learning context- dependent personal preferences from a wearable sensor array

A. Krause, A. Smailagic, D.P. Siewiorek
<span title="">2006</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/m6d55yg2wncgnomdnlvb6ofsmq" style="color: black;">IEEE Transactions on Mobile Computing</a> </i> &nbsp;
This learning occurs online and does not require external supervision. The system relies on techniques from machine learning and statistical analysis.  ...  Context-aware computing describes the situation where a wearable/mobile computer is aware of its user's state and surroundings and modifies its behavior based on this information.  ...  ACKNOWLEDGMENTS The authors would like to acknowledge all students working on the SenSay project, especially Neema Moraveji for his work on [15] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tmc.2006.18">doi:10.1109/tmc.2006.18</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6h2up3aqr5gvnjwophtrnxahp4">fatcat:6h2up3aqr5gvnjwophtrnxahp4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20060627100727/http://interruptions.net:80/literature/Krause-TMC06-h0113.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/98/e7/98e7d2734ed74d28e42a9fa3c8aef78929587dc3.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tmc.2006.18"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

An Optimal DF Based Method for Transient Stability Analysis

Z. A. Zaki, Emad M. Ahmed, Ziad M. Ali, Imran Khan
<span title="">2022</span> <i title="Computers, Materials and Continua (Tech Science Press)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/amujz7fcqna6do727z6ev3ueo4" style="color: black;">Computers Materials &amp; Continua</a> </i> &nbsp;
The weighted voting technique is used in the learning process to increase the classification accuracy of unstable samples.  ...  The effect of energy on the natural environment has become increasingly severe as human consumption of fossil energy has increased.  ...  The second is to construct an initial feature set based on the combined variables of the system parameters before and after the fault.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.32604/cmc.2022.020263">doi:10.32604/cmc.2022.020263</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qbfnlojwonhphnzfhakrubpn34">fatcat:qbfnlojwonhphnzfhakrubpn34</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220223163126/https://www.techscience.com/ueditor/files/cmc/TSP_CMC_70-2/TSP_CMC_20263/TSP_CMC_20263.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/06/85/06858f34787b2b08f90c2c9a52a929598d41aeb6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.32604/cmc.2022.020263"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Implementation of a Massively Parallel Dynamic Security Assessment Platform for Large-Scale Grids

Ioannis Konstantelos, Geoffroy Jamgotchian, Simon Tindemans, Philippe Duchesne, Stijn Cole, Christian Merckx, Goran Strbac, Partick Panciatici
<span title="">2018</span> <i title="IEEE"> 2018 IEEE Power &amp; Energy Society General Meeting (PESGM) </i> &nbsp;
This paper presents a computational platform for dynamic security assessment (DSA) of large electricity grids, developed as part of the iTesla project.  ...  A case study of the French grid is presented, with over 8000 scenarios and 1980 contingencies.  ...  The authors would also like to thank all iTesla partners for their contribution to platform development.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/pesgm.2018.8586141">doi:10.1109/pesgm.2018.8586141</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zszfmd7hpraf7mcwpatvu3fj3m">fatcat:zszfmd7hpraf7mcwpatvu3fj3m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180719131145/http://spiral.imperial.ac.uk/bitstream/10044/1/39765/2/IEEE_TSG_HPC_Final.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/03/6a/036aa2608b89a731d37d0316169875fb948a339b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/pesgm.2018.8586141"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

A Novel Hybrid Brain-Computer Interface Combining Motor Imagery and Intermodulation Steady-State Visual Evoked Potential

Xinyi Chi, Chunxiao Wan, Chunyan Wang, Yong Zhang, Xiaogang Chen, Hongyan Cui
<span title="2022-06-03">2022</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kujklva47vealdwew7xiv34ble" style="color: black;">IEEE transactions on neural systems and rehabilitation engineering</a> </i> &nbsp;
The high recognition accuracy verifies the feasibility and robustness of the proposed system. This study provides a novel and natural paradigm for a hybrid BCI based on MI and SSVEP.  ...  The online verification results showed that the average accuracies of 12 healthy subjects and 11 stroke patients were 92.40 ± 7.45% and 73.07 ± 9.07%, respectively.  ...  Experimental Environment 1) Subjects This study involved an offline experiment for parameter optimization, an online verification experiment, and an online comparative experiment.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tnsre.2022.3179971">doi:10.1109/tnsre.2022.3179971</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/35657833">pmid:35657833</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dtbckbzawvh3tkbzexfc44wlum">fatcat:dtbckbzawvh3tkbzexfc44wlum</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220609063921/https://ieeexplore.ieee.org/ielx7/7333/4359219/09787489.pdf?tp=&amp;arnumber=9787489&amp;isnumber=4359219&amp;ref=" 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/03/37/03375a1c20d8af2a5c24e9713f9a4d548e36de0c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tnsre.2022.3179971"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

A literature review on one-class classification and its potential applications in big data

Naeem Seliya, Azadeh Abdollah Zadeh, Taghi M. Khoshgoftaar
<span title="2021-09-10">2021</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/pkhnkszyprhb3orbf6g7tqmgiu" style="color: black;">Journal of Big Data</a> </i> &nbsp;
One-class classification (OCC) is an approach to detect abnormal data points compared to the instances of the known class and can serve to address issues related to severely imbalanced datasets, which  ...  AbstractIn severely imbalanced datasets, using traditional binary or multi-class classification typically leads to bias towards the class(es) with the much larger number of instances.  ...  Acknowledgements We would like to thank the various reviewers in the Data Mining and Machine Learning Laboratory at Florida Atlantic University, Boca Raton, FL 33431.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s40537-021-00514-x">doi:10.1186/s40537-021-00514-x</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/iaqfshjii5butmn64yrecd5yxq">fatcat:iaqfshjii5butmn64yrecd5yxq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211204022131/https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-021-00514-x.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/f2/af/f2af44ecbdfa1ae82b623f42d58e16e5e5cd2e67.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s40537-021-00514-x"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a>

Demonstration

Peter Bailis, Edward Gan, Kexin Rong, Sahaana Suri
<span title="">2017</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vxrc3vebzzachiwy3nopwi3h5u" style="color: black;">Proceedings of the 2017 ACM International Conference on Management of Data - SIGMOD &#39;17</a> </i> &nbsp;
In this demonstration, SIGMOD attendees will have the opportunity to interactively answer and refine queries using MacroBase and discover the potential benefits of an advanced engine for prioritizing attention  ...  MacroBase provides a set of highlyoptimized, modular operators for streaming feature transformation, classification, and explanation.  ...  In the parlance of machine learning, this corresponds to a combination of streaming classification and explanation techniques, at scale.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/3035918.3056446">doi:10.1145/3035918.3056446</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/sigmod/BailisGRS17.html">dblp:conf/sigmod/BailisGRS17</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/agybb7bbabempk2atxjhekoszq">fatcat:agybb7bbabempk2atxjhekoszq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190218144729/https://static.aminer.org/pdf/20170130/pdfs/sigmod/btj98rq0udawrcp5goj13fkgv7azvhhx.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/c1/d7c141c9290998c002cf5db3bb95e9ae044a1f7b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/3035918.3056446"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Industrial data science – a review of machine learning applications for chemical and process industries

Max Mowbray, Mattia Vallerio, Carlos Perez-Galvan, Dongda Zhang, Antonio Del Rio Chanona, Francisco J. Navarro-Brull
<span title="">2022</span> <i title="Royal Society of Chemistry (RSC)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dbj3gqskhjbwpnj5hmhzdrboqq" style="color: black;">Reaction Chemistry &amp; Engineering</a> </i> &nbsp;
Understand and optimize industrial processes via machine learning and chemical engineering principles.  ...  Acknowledgements The authors appreciate the support from JMP (SAS Institute Inc.) for facilitating the open access of this manuscript.  ...  Perhaps the most obvious example of this is the training of neural networks, which are commonplace within the SI toolbox. 138 .4.2 Machine learning for dynamical systems modeling.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1039/d1re00541c">doi:10.1039/d1re00541c</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/q7ielo4h2bgudlypi4vjd4aajm">fatcat:q7ielo4h2bgudlypi4vjd4aajm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220423232058/https://pubs.rsc.org/en/content/articlepdf/2022/re/d1re00541c" 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/99/1e/991e92c216cad9e488c7ba09d16c55ed89d0bd2b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1039/d1re00541c"> <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>

Advancing Neuromorphic Computing With Loihi: A Survey of Results and Outlook

Mike Davies, Andreas Wild, Garrick Orchard, Yulia Sandamirskaya, Gabriel A. Fonseca Guerra, Prasad Joshi, Philipp Plank, Sumedh R. Risbud
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/yfvtieuumfamvmjlc255uckdlm" style="color: black;">Proceedings of the IEEE</a> </i> &nbsp;
that is natively suited for classes of brain-inspired computation that challenge the von Neumann model.  ...  The rethinking of computing that results from this pursuit intersects in unexpected ways with relevant fields, such as machine learning, deep learning, artificial intelligence, computational science, and  ...  As the first step, instances of the delta rule 2 Δw ∝ xpre · σ post · δypost for single-layer online learning have been demonstrated on Loihi, including Surrogate Online Error Learning (SOEL) [49] and  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/jproc.2021.3067593">doi:10.1109/jproc.2021.3067593</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/krqdmy3u6jdvfl7btjglek5ag4">fatcat:krqdmy3u6jdvfl7btjglek5ag4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210717223515/https://ieeexplore.ieee.org/ielx7/5/9420072/09395703.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/5e/68/5e68382b320413fc7672ed019eb0a807baf76f1e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/jproc.2021.3067593"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>
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