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Data Science for Public Policy / Jeffrey C. Chen, Edward A. Rubin, Gary J. Cornwall
| Data Science for Public Policy / Jeffrey C. Chen, Edward A. Rubin, Gary J. Cornwall |
| Autore | Chen, Jeffrey C. |
| Pubbl/distr/stampa | Cham, : Springer, 2021 |
| Descrizione fisica | xiv, 363 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Cornwall, Gary J.
Rubin, Edward A. |
| Soggetto topico |
68-XX - Computer science [MSC 2020]
62H12 - Estimation in multivariate analysis [MSC 2020] 62-XX - Statistics [MSC 2020] 62J05 - Linear regression; mixed models [MSC 2020] 62H11 - Directional data; spatial statistics [MSC 2020] 68N15 - Theory of programming languages [MSC 2020] 91-XX - Game theory, economics, finance, and other social and behavioral sciences [MSC 2020] 62P20 - Applications of statistics to economics [MSC 2020] 62J07 - Ridge regression; shrinkage estimators (Lasso) [MSC 2020] 62P25 - Applications of statistics to social sciences [MSC 2020] 62P12 - Applications of statistics to environmental and related topics [MSC 2020] 68T50 - Natural language processing [MSC 2020] 91C20 - Clustering in the social and behavioral sciences [MSC 2020] 68N01 - General topics in the theory of software [MSC 2020] |
| Soggetto non controllato |
Data Sciences
Econometrics Programming Public policy Statistics |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0274696 |
Chen, Jeffrey C.
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| Cham, : Springer, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Data Science for Public Policy / Jeffrey C. Chen, Edward A. Rubin, Gary J. Cornwall
| Data Science for Public Policy / Jeffrey C. Chen, Edward A. Rubin, Gary J. Cornwall |
| Autore | Chen, Jeffrey C. |
| Pubbl/distr/stampa | Cham, : Springer, 2021 |
| Descrizione fisica | xiv, 363 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Cornwall, Gary J.
Rubin, Edward A. |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62H11 - Directional data; spatial statistics [MSC 2020] 62H12 - Estimation in multivariate analysis [MSC 2020] 62J05 - Linear regression; mixed models [MSC 2020] 62J07 - Ridge regression; shrinkage estimators (Lasso) [MSC 2020] 62P12 - Applications of statistics to environmental and related topics [MSC 2020] 62P20 - Applications of statistics to economics [MSC 2020] 62P25 - Applications of statistics to social sciences [MSC 2020] 68-XX - Computer science [MSC 2020] 68N01 - General topics in the theory of software [MSC 2020] 68N15 - Theory of programming languages [MSC 2020] 68T50 - Natural language processing [MSC 2020] 91-XX - Game theory, economics, finance, and other social and behavioral sciences [MSC 2020] 91C20 - Clustering in the social and behavioral sciences [MSC 2020] |
| Soggetto non controllato |
Data Sciences
Econometrics Programming Public policy Statistics |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00274696 |
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Chen, Jeffrey C.
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| Cham, : Springer, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Fundamentals of High-Dimensional Statistics : With Exercises and R Labs / Johannes Lederer
| Fundamentals of High-Dimensional Statistics : With Exercises and R Labs / Johannes Lederer |
| Autore | Lederer, Johannes |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | xiv, 355 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62H22 - Probabilistic graphical models [MSC 2020] 62J07 - Ridge regression; shrinkage estimators (Lasso) [MSC 2020] 62R07 - Statistical aspects of big data and data science [MSC 2020] |
| Soggetto non controllato |
Calibration
Estimation Graphical Models High dimensional inference High-Dimensional Data High-dimensional statistics Lasso Linear regression Prediction R labs Regularization Sparsity Statistical inference |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0277448 |
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Lederer, Johannes
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| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Fundamentals of High-Dimensional Statistics : With Exercises and R Labs / Johannes Lederer
| Fundamentals of High-Dimensional Statistics : With Exercises and R Labs / Johannes Lederer |
| Autore | Lederer, Johannes |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | xiv, 355 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62H22 - Probabilistic graphical models [MSC 2020] 62J07 - Ridge regression; shrinkage estimators (Lasso) [MSC 2020] 62R07 - Statistical aspects of big data and data science [MSC 2020] |
| Soggetto non controllato |
Calibration
Estimation Graphical Models High dimensional inference High-Dimensional Data High-dimensional statistics Lasso Linear regression Prediction R labs Regularization Sparsity Statistical inference |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00277448 |
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Lederer, Johannes
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| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Generalized principal component analysis / René Vidal, Yi Ma, S. Shankar Sastry
| Generalized principal component analysis / René Vidal, Yi Ma, S. Shankar Sastry |
| Autore | Vidal, René |
| Pubbl/distr/stampa | New York, : Springer, 2016 |
| Descrizione fisica | XXXII, 566 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Ma, Yi
Sastry, S. Shankar |
| Soggetto topico |
14-XX - Algebraic geometry [MSC 2020]
15-XX - Linear and multilinear algebra; matrix theory [MSC 2020] 62B10 - Statistical aspects of information-theoretic topics [MSC 2020] 62H12 - Estimation in multivariate analysis [MSC 2020] 62-XX - Statistics [MSC 2020] 62J05 - Linear regression; mixed models [MSC 2020] 30C10 - Polynomials and rational functions of one complex variable [MSC 2020] 62H35 - Image analysis in multivariate analysis [MSC 2020] 62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020] 62Jxx - Linear inference, regression [MSC 2020] 62J07 - Ridge regression; shrinkage estimators (Lasso) [MSC 2020] 62Fxx - Parametric inference [MSC 2020] 30C40 - Kernel functions in one complex variable and applications [MSC 2020] 14N20 - Configurations and arrangements of linear subspaces [MSC 2020] |
| Soggetto non controllato |
Hybrid system identification
Image and video segmentation Linear subspace models Low-rank matrix theory Manifold learning Principal component analysis Robust principal component analysis Sparse representation theory Spectral clustering Subspace arrangements Subspace clustering |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0114796 |
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Vidal, René
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| New York, : Springer, 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Generalized principal component analysis / René Vidal, Yi Ma, S. Shankar Sastry
| Generalized principal component analysis / René Vidal, Yi Ma, S. Shankar Sastry |
| Autore | Vidal, René |
| Pubbl/distr/stampa | New York, : Springer, 2016 |
| Descrizione fisica | XXXII, 566 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Ma, Yi
Sastry, S. Shankar |
| Soggetto topico |
14-XX - Algebraic geometry [MSC 2020]
14N20 - Configurations and arrangements of linear subspaces [MSC 2020] 15-XX - Linear and multilinear algebra; matrix theory [MSC 2020] 30C10 - Polynomials and rational functions of one complex variable [MSC 2020] 30C40 - Kernel functions in one complex variable and applications [MSC 2020] 62-XX - Statistics [MSC 2020] 62B10 - Statistical aspects of information-theoretic topics [MSC 2020] 62Fxx - Parametric inference [MSC 2020] 62H12 - Estimation in multivariate analysis [MSC 2020] 62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020] 62H35 - Image analysis in multivariate analysis [MSC 2020] 62J05 - Linear regression; mixed models [MSC 2020] 62J07 - Ridge regression; shrinkage estimators (Lasso) [MSC 2020] 62Jxx - Linear inference, regression [MSC 2020] |
| Soggetto non controllato |
Hybrid system identification
Image and video segmentation Linear subspace models Low-rank matrix theory Manifold learning Principal component analysis Robust principal component analysis Sparse representation theory Spectral clustering Subspace arrangements Subspace clustering |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00114796 |
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Vidal, René
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| New York, : Springer, 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Generalized principal component analysis / René Vidal, Yi Ma, S. Shankar Sastry
| Generalized principal component analysis / René Vidal, Yi Ma, S. Shankar Sastry |
| Autore | Vidal, René |
| Edizione | [New York : Springer, 2016] |
| Pubbl/distr/stampa | XXXII, 566 p., : ill. ; 24 cm |
| Descrizione fisica | Pubblicazione in formato elettronico |
| Altri autori (Persone) |
Ma, Yi
Sastry, S. Shankar |
| Soggetto topico |
14-XX - Algebraic geometry [MSC 2020]
15-XX - Linear and multilinear algebra; matrix theory [MSC 2020] 62B10 - Statistical aspects of information-theoretic topics [MSC 2020] 62H12 - Estimation in multivariate analysis [MSC 2020] 62-XX - Statistics [MSC 2020] 62J05 - Linear regression; mixed models [MSC 2020] 30C10 - Polynomials and rational functions of one complex variable [MSC 2020] 62H35 - Image analysis in multivariate analysis [MSC 2020] 62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020] 62Jxx - Linear inference, regression [MSC 2020] 62J07 - Ridge regression; shrinkage estimators (Lasso) [MSC 2020] 62Fxx - Parametric inference [MSC 2020] 30C40 - Kernel functions in one complex variable and applications [MSC 2020] 14N20 - Configurations and arrangements of linear subspaces [MSC 2020] |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-SUN0114796 |
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Vidal, René
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| XXXII, 566 p., : ill. ; 24 cm | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Machine Learning Algorithms : Adversarial Robustness in Signal Processing / Fuwei Li, Lifeng Lai, Shuguang Cui
| Machine Learning Algorithms : Adversarial Robustness in Signal Processing / Fuwei Li, Lifeng Lai, Shuguang Cui |
| Autore | Li, Fuwei |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | ix, 104 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Cui, Shuguang
Lai, Lifeng |
| Soggetto topico |
62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020]
62J05 - Linear regression; mixed models [MSC 2020] 62J07 - Ridge regression; shrinkage estimators (Lasso) [MSC 2020] 68-XX - Computer science [MSC 2020] 68M18 - Wireless sensor networks as related to computer science [MSC 2020] 68M25 - Computer security [MSC 2020] 68T05 - Learning and adaptive systems in artificial intelligence [MSC 2020] 94A12 - Signal theory (characterization, reconstruction, filtering, etc.) [MSC 2020] |
| Soggetto non controllato |
Adversarial attack
Adversarial machine learning Adversarial robustness Alternating optimization Bi-level optimization Interpretable machine learning Linear regression Machine learning Non-convex optimization Principal component analysis Security-critical machine learning Signal processing Subspace learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0277808 |
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Li, Fuwei
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| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Machine Learning Algorithms : Adversarial Robustness in Signal Processing / Fuwei Li, Lifeng Lai, Shuguang Cui
| Machine Learning Algorithms : Adversarial Robustness in Signal Processing / Fuwei Li, Lifeng Lai, Shuguang Cui |
| Autore | Li, Fuwei |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | ix, 104 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Cui, Shuguang
Lai, Lifeng |
| Soggetto topico |
62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020]
62J05 - Linear regression; mixed models [MSC 2020] 62J07 - Ridge regression; shrinkage estimators (Lasso) [MSC 2020] 68-XX - Computer science [MSC 2020] 68M18 - Wireless sensor networks as related to computer science [MSC 2020] 68M25 - Computer security [MSC 2020] 68T05 - Learning and adaptive systems in artificial intelligence [MSC 2020] 94A12 - Signal theory (characterization, reconstruction, filtering, etc.) [MSC 2020] |
| Soggetto non controllato |
Adversarial attack
Adversarial machine learning Adversarial robustness Alternating optimization Bi-level optimization Interpretable machine learning Linear regression Machine learning Non-convex optimization Principal component analysis Security-critical machine learning Signal processing Subspace learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00277808 |
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Li, Fuwei
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| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Penalty, shrinkage and pretest strategies : variable selection and estimation / S. Ejaz Ahmed
| Penalty, shrinkage and pretest strategies : variable selection and estimation / S. Ejaz Ahmed |
| Autore | Ahmed, Syed Ejaz |
| Pubbl/distr/stampa | Cham, : Springer, 2014 |
| Descrizione fisica | IX, 115 p. : ill. ; 24 cm |
| Soggetto topico |
62F10 - Point estimation [MSC 2020]
62J05 - Linear regression; mixed models [MSC 2020] 62F12 - Asymptotic properties of parametric estimators [MSC 2020] 62J07 - Ridge regression; shrinkage estimators (Lasso) [MSC 2020] |
| Soggetto non controllato |
Penalty estimation
Pooling data Pretest and shrinkage estimation Regression models Variable Selection |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0103264 |
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Ahmed, Syed Ejaz
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| Cham, : Springer, 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Soggetto topico
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62J07 - Ridge regression; shrinkage estimators (Lasso) [MSC 2020]
(17)
- 62J05 - Linear regression; mixed models [MSC 2020] (14)
- 62-XX - Statistics [MSC 2020] (12)
- 62H12 - Estimation in multivariate analysis [MSC 2020] (5)
- 62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020] (5)