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  • Search: subject:"l1-regularization"
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Year of publication
Subject
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Estimation theory 5 Schätztheorie 5 l1-regularization 5 Portfolio selection 4 Portfolio-Management 4 Mathematical programming 3 Mathematische Optimierung 3 Theorie 3 Theory 3 CAPM 2 Correlation 2 Factor analysis 2 Faktorenanalyse 2 Korrelation 2 L1 regularization 2 L1-regularization 2 portfolio allocation 2 weak factors 2 Adaptive LASSO 1 Alternating direction method of multipliers 1 Analysis of variance 1 Approximate Factor model 1 Efficiency 1 Effizienz 1 Estimation 1 Factor-augmented VAR model 1 Fixed-effect stochastic frontier model 1 Geldpolitik 1 Geldpolitische Transmission 1 Impact assessment 1 Lasso 1 Lazy lasso 1 Linear algebra 1 Lineare Algebra 1 Locally weighted regression 1 Loess 1 Mean-variance portfolio selection 1 Monetary policy 1 Monetary policy shock 1 Monetary transmission 1
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Online availability
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Free 5 Undetermined 5
Type of publication
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Article 6 Book / Working Paper 4
Type of publication (narrower categories)
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Article in journal 4 Aufsatz in Zeitschrift 4 Arbeitspapier 3 Graue Literatur 3 Non-commercial literature 3 Working Paper 3 Aufsatz im Buch 1 Book section 1
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Language
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English 8 Undetermined 2
Author
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Daniele, Maurizio 3 Pohlmeier, Winfried 2 Zagidullina, Aygul 2 Bielza, Concha 1 Bradic, Jelena 1 Chen, Jingnan 1 Chen, Xiaojun 1 Claeskens, Gerda 1 Dai, Gengling 1 Dai, Zhifeng 1 Horrace, William C. 1 Jung, Hyunseok 1 Kang, Jie 1 Larrañaga, Pedro 1 Lee, Yoonseok 1 Lu, Zhaosong 1 NESTEROV, Yu. 1 Schnaitmann, Julie 1 Vidaurre, Diego 1 Zhang, Ning 1 Zhou, Jing 1
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Institution
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Center for Operations Research and Econometrics (CORE), École des Sciences Économiques de Louvain 1
Published in...
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Annals of operations research ; volume 284, numbers 1 (January 2020) 1 CORE Discussion Papers 1 Computational Statistics 1 GSDS working paper 1 International journal of finance & economics : IJFE 1 Journal of business & economic statistics : JBES ; a publication of the American Statistical Association 1 KBI 1 Mathematics of operations research 1 Working papers 1
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Source
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ECONIS (ZBW) 8 RePEc 2
Showing 1 - 10 of 10
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A sparse approximate factor model for high-dimensional covariance matrix estimation and portfolio selection
Daniele, Maurizio; Pohlmeier, Winfried; Zagidullina, Aygul - 2025
Persistent link: https://www.econbiz.de/10015339161
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LASSO for stochastic frontier models with many efficient firms
Horrace, William C.; Jung, Hyunseok; Lee, Yoonseok - In: Journal of business & economic statistics : JBES ; a … 41 (2023) 4, pp. 1132-1142
Persistent link: https://www.econbiz.de/10014448583
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Sparse approximate factor estimation for high-dimensional covariance matrices
Daniele, Maurizio; Pohlmeier, Winfried; Zagidullina, Aygul - 2020
Persistent link: https://www.econbiz.de/10012317378
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Detangling robustness in high-dimensions : composite versus model-averaged estimation
Zhou, Jing; Claeskens, Gerda; Bradic, Jelena - 2020
Persistent link: https://www.econbiz.de/10012439264
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A regularized structural factor-augmented vector autoregressive model
Daniele, Maurizio; Schnaitmann, Julie - 2019
Persistent link: https://www.econbiz.de/10012122962
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Some new efficient mean-variance portfolio selection models
Dai, Zhifeng; Kang, Jie - In: International journal of finance & economics : IJFE 27 (2022) 4, pp. 4784-4796
Persistent link: https://www.econbiz.de/10013461378
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An application of sparse-group lasso regularization to equity portfolio optimization and sector selection
Chen, Jingnan; Dai, Gengling; Zhang, Ning - 2020
Persistent link: https://www.econbiz.de/10012165565
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Generalized conjugate gradient methods for l1 regularized convex quadratic programming with finite convergence
Lu, Zhaosong; Chen, Xiaojun - In: Mathematics of operations research 43 (2018) 1, pp. 275-303
Persistent link: https://www.econbiz.de/10011818761
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Gradient methods for minimizing composite objective function
NESTEROV, Yu. - Center for Operations Research and Econometrics (CORE), … - 2007
In this paper we analyze several new methods for solving optimization problems with the objective function formed as a sum of two convex terms: one is smooth and given by a black-box oracle, and another is general but simple and its structure is known. Despite to the bad properties of the sum,...
Persistent link: https://www.econbiz.de/10005008277
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Lazy lasso for local regression
Vidaurre, Diego; Bielza, Concha; Larrañaga, Pedro - In: Computational Statistics 27 (2012) 3, pp. 531-550
Locally weighted regression is a technique that predicts the response for new data items from their neighbors in the training data set, where closer data items are assigned higher weights in the prediction. However, the original method may suffer from overfitting and fail to select the relevant...
Persistent link: https://www.econbiz.de/10010998498
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