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  • Search: subject:"Supervised Learning"
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Year of publication
Subject
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supervised learning 75 Artificial intelligence 68 Künstliche Intelligenz 63 Supervised learning 58 Learning process 56 Lernprozess 56 Learning 43 Lernen 43 Theorie 43 Theory 42 Forecasting model 35 Prognoseverfahren 35 machine learning 29 Machine learning 23 Classification 18 Algorithm 17 Algorithmus 17 Data mining 17 Neural networks 17 Neuronale Netze 17 Semi-supervised learning 17 Data Mining 15 Supervised Learning 15 Klassifikation 14 Learning organization 13 Lernende Organisation 13 classification 11 Pattern recognition 9 deep learning 9 unsupervised learning 8 Estimation 7 Mustererkennung 7 Schätzung 7 USA 7 United States 7 semi-supervised learning 7 Mathematical programming 6 Mathematische Optimierung 6 Social Web 6 Social web 6
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Online availability
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Undetermined 111 Free 80 CC license 12
Type of publication
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Article 160 Book / Working Paper 35
Type of publication (narrower categories)
All
Article in journal 106 Aufsatz in Zeitschrift 106 Working Paper 30 Arbeitspapier 17 Graue Literatur 17 Non-commercial literature 17 Article 14 Aufsatz im Buch 6 Book section 6 research-article 3 Conference paper 1 Konferenzbeitrag 1 Lehrbuch 1
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Language
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English 167 Undetermined 24 German 2 French 1 Portuguese 1
Author
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Niggli, Matthias 5 Nowak, Adam 5 Askitas, Nikos 4 Frejinger, Emma 4 Rutzer, Christian 4 Abudu, Bolanle 3 Boulesteix, Anne-Laure 3 Burgard, Jan Pablo 3 Humphreys, Brad R. 3 Lange, Tatjana 3 Lodi, Andrea 3 Mosler, Karl 3 Mozharovskyi, Pavlo 3 Nomaler, Önder 3 Pinheiro, Maria Eduarda 3 Verspagen, Bart 3 Zhou, Yang 3 Adıvar, Murat 2 Albert, Maximilian 2 Antos, Sarah Elizabeth 2 Arbabi, Farzin 2 Avner, Paolo 2 Bembom, Oliver 2 Bengio, Yoshua 2 Bengtsson, Linus 2 Biegel, Tobias 2 Brooks, Christopher J. 2 Burci, Priya 2 Chen, Jun 2 Cordier, Johannes 2 Debener, Jörn 2 Ebrahimi, Pejman 2 Fan, Jianqing 2 Gensicke, Miriam 2 Gonzalez, Miguel 2 Gray, Jonathan 2 Hall, Joshua C. 2 He, Mengxi 2 Heinisch, Dominik 2 Heinke, Volker 2
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Institution
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Banco de México 1 Centre Interuniversitaire de Recherche en Analyse des Organisations (CIRANO) 1 Seminar für Wirtschafts- und Sozialstatistik, Wirtschafts- und Sozialwissenschaftliche Fakultät 1 Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München 1
Published in...
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Computational economics 5 INFORMS journal on computing : JOC ; charting new directions in operations research and computer science ; a journal of the Institute for Operations Research and the Management Sciences 5 Journal of marketing analytics : JMA 5 Journal of Intelligent Manufacturing 4 Statistical Applications in Genetics and Molecular Biology 4 European journal of operational research : EJOR 3 International journal of production economics 3 International journal of production research 3 The journal of risk & insurance 3 Working papers / Department of Economics, West Virginia University 3 Computational Statistics & Data Analysis 2 Computers & operations research : an international journal 2 Data science and management : DSM 2 Energy economics 2 IAB discussion paper : Beiträge zum wissenschaftlichen Dialog aus dem Institut für Arbeitsmarkt- und Berufsforschung 2 IAB-Discussion Paper 2 International Journal of Data Analysis Techniques and Strategies 2 International journal of business information systems : IJBIS 2 International journal of financial engineering 2 Journal of forecasting 2 Mathematics and Computers in Simulation (MATCOM) 2 Physica A: Statistical Mechanics and its Applications 2 Risks : open access journal 2 UNU-MERIT Working Papers 2 WWZ Working Paper 2 WWZ working paper 2 Annals of operations research ; volume 287, number 1 (April 2020) 1 Applied economics 1 Applied economics letters 1 Asia-Pacific journal of management research and innovation 1 Borradores de economía 1 Business & information systems engineering 1 CESifo Working Paper 1 CESifo working papers 1 CIRANO Working Papers 1 China economic review : an international journal 1 Computational Optimization and Applications 1 Computational Statistics 1 Computers & operations research : and their applications to problems of world concern ; an international journal 1 Contemporary studies of risks in emerging technology, part A 1
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Source
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ECONIS (ZBW) 130 EconStor 27 RePEc 27 Other ZBW resources 10 BASE 1
Showing 11 - 20 of 195
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Mixed-integer quadratic optimization and iterative clustering techniques for semi-supervised support vector machines
Burgard, Jan Pablo; Pinheiro, Maria Eduarda; Schmidt, Martin - In: Top : an official journal of the Spanish Society of … 32 (2024) 3, pp. 391-428
Persistent link: https://www.econbiz.de/10015188200
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Improving demand forecasting for customers with missing downstream data in intermittent demand supply chains with supervised multivariate clustering
Ducharme, Corey; Agard, Bruno; Trépanier, Martin - In: Journal of forecasting 43 (2024) 5, pp. 1661-1681
Persistent link: https://www.econbiz.de/10015108428
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A hands-on machine learning primer for social scientists : math, algorithms and code
Askitas, Nikos - 2024
This paper addresses the steep learning curve in Machine Learning faced by non-computer scientists, particularly social scientists, stemming from the absence of a primer on its fundamental principles. I adopt a pedagogical strategy inspired by the adage ”once you understand OLS, you can work...
Persistent link: https://www.econbiz.de/10015070152
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Research on the application of virtual reality technology in the cultural exchange of tourist attractions under the background of artificial intelligence
Hou, Na - In: International journal of information systems and supply … 17 (2024) 1, pp. 1-19
Persistent link: https://www.econbiz.de/10015433056
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Predicting patent quality based on machine learning approach
Erdogan, Zulfiye; Altuntas, Serkan; Dereli, Türkay - In: IEEE transactions on engineering management : EM ; a … 71 (2024), pp. 3144-3157
Persistent link: https://www.econbiz.de/10015405946
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A Hands-On Machine Learning Primer for Social Scientists: Math, Algorithms and Code
Askitas, Nikos - 2024
This paper addresses the steep learning curve in Machine Learning faced by non-computer scientists, particularly social scientists, stemming from the absence of a primer on its fundamental principles. I adopt a pedagogical strategy inspired by the adage ”once you understand OLS, you can work...
Persistent link: https://www.econbiz.de/10015096855
Saved in:
Cover Image
Mixed-integer quadratic optimization and iterative clustering techniques for semi-supervised support vector machines
Burgard, Jan Pablo; Pinheiro, Maria Eduarda; Schmidt, Martin - In: TOP 32 (2024) 3, pp. 391-428
Among the most famous algorithms for solving classification problems are support vector machines (SVMs), which find a separating hyperplane for a set of labeled data points. In some applications, however, labels are only available for a subset of points. Furthermore, this subset can be...
Persistent link: https://www.econbiz.de/10015375768
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Convergence of a quasi-Newton method for solving systems of nonlinear underdetermined equations
Vater, N.; Borzì, A. - In: Computational Optimization and Applications 91 (2024) 2, pp. 973-996
underdetermined equations is investigated. These equations arise in many application fields, e.g., supervised learning of large … problems and supervised learning of overparameterised neural networks. …
Persistent link: https://www.econbiz.de/10015436625
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Maschinelles Lernen im Basisregister für Unternehmen: Vorstudie zum Potenzial automatischer Konsolidierung von Unternehmensstammdaten
Weißmann, Julius; Herbst, Tim - In: WISTA - Wirtschaft und Statistik 76 (2024) 3, pp. 67-79
Das Statistische Bundesamt hat den gesetzlichen Auftrag, ein Register über Unter nehmensbasisdaten für Deutschland aufzubauen. Die Inhalte und Ziele des Basisre gisters für Unternehmen werden in dem zugrunde liegenden Gesetz definiert. Diese liegen vor allem in der Konsolidierung der...
Persistent link: https://www.econbiz.de/10014560159
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A Hands-on Machine Learning Primer for Social Scientists: Math, Algorithms and Code
Askitas, Nikos - 2024
This paper addresses the steep learning curve in Machine Learning faced by noncomputer scientists, particularly social scientists, stemming from the absence of a primer on its fundamental principles. I adopt a pedagogical strategy inspired by the adage "once you understand OLS, you can work your...
Persistent link: https://www.econbiz.de/10014567597
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