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Learning process 2 Lernprozess 2 Theorie 2 Theory 2 Active sets 1 Alternating least squares 1 L0-regularized learning 1 Learning 1 Learning organization 1 Lernen 1 Lernende Organisation 1 Mathematical programming 1 Mathematische Optimierung 1 Microeconometrics 1 Mikroökonometrie 1 Non-monotone technique 1 Non-negative matrix factorization 1 Regression analysis 1 Regressionsanalyse 1 active sets 1 global and local optimizers 1 high-dimensional features 1 learning 1 model selection consistency 1 primal dual active sets 1 survival data analysis 1
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Undetermined 3
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Article 3
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Article in journal 2 Aufsatz in Zeitschrift 2
Language
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English 2 Undetermined 1
Author
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Li, Xiangli 1 Li, Yang 1 Liu, Hongwei 1 Misra, Sidhant 1 Ng, Yeesian 1 Roald, Line 1 Zhang, Jie 1 Zheng, Zemin 1
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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 2 Computational Optimization and Applications 1
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ECONIS (ZBW) 2 RePEc 1
Showing 1 - 3 of 3
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L0-regularized learning for high-dimensional additive hazards regression
Zheng, Zemin; Zhang, Jie; Li, Yang - In: INFORMS journal on computing : JOC ; charting new … 34 (2022) 5, pp. 2762-2775
Persistent link: https://www.econbiz.de/10014325578
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Learning for constrained optimization : identifying optimal active constraint sets
Misra, Sidhant; Roald, Line; Ng, Yeesian - In: INFORMS journal on computing : JOC ; charting new … 34 (2022) 1, pp. 463-480
Persistent link: https://www.econbiz.de/10013359102
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Modified subspace Barzilai-Borwein gradient method for non-negative matrix factorization
Liu, Hongwei; Li, Xiangli - In: Computational Optimization and Applications 55 (2013) 1, pp. 173-196
Non-negative matrix factorization (NMF) is a problem to obtain a representation of data using non-negativity constraints. Since the NMF was first proposed by Lee, NMF has attracted much attention for over a decade and has been successfully applied to numerous data analysis problems. Recent...
Persistent link: https://www.econbiz.de/10010680665
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