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Advanced Data Analysis in Neuroscience : Integrating Statistical and Computational Models / Daniel Durstewitz
| Advanced Data Analysis in Neuroscience : Integrating Statistical and Computational Models / Daniel Durstewitz |
| Autore | Durstewitz, Daniel |
| Pubbl/distr/stampa | Cham, : Springer, 2017 |
| Descrizione fisica | xxv, 292 p. : ill. ; 24 cm |
| Soggetto topico |
92C20 - Neural biology [MSC 2020]
62R07 - Statistical aspects of big data and data science [MSC 2020] 68T09 - Computational aspects of data analysis and big data [MSC 2020] |
| Soggetto non controllato |
Bootstrap methods
Change point analysis Clustering Dimensionality reduction Machine learning Multiple testing Multivariate maps and recurrent neural networks Multivariate statistics Neural time series Nonlinear dynamical systems Nonlinear oscillations Nonparametric time series modeling Principal component analysis Reconstructing state spaces from experimental data Statistical methods in neuroscience Statistical parameter estimation Unsupervised clustering |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0123545 |
Durstewitz, Daniel
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| Cham, : Springer, 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Advanced Data Analysis in Neuroscience : Integrating Statistical and Computational Models / Daniel Durstewitz
| Advanced Data Analysis in Neuroscience : Integrating Statistical and Computational Models / Daniel Durstewitz |
| Autore | Durstewitz, Daniel |
| Pubbl/distr/stampa | Cham, : Springer, 2017 |
| Descrizione fisica | xxv, 292 p. : ill. ; 24 cm |
| Soggetto topico |
62R07 - Statistical aspects of big data and data science [MSC 2020]
68T09 - Computational aspects of data analysis and big data [MSC 2020] 92C20 - Neural biology [MSC 2020] |
| Soggetto non controllato |
Bootstrap methods
Change point analysis Clustering Dimensionality reduction Machine learning Multiple testing Multivariate maps and recurrent neural networks Multivariate statistics Neural time series Nonlinear dynamical systems Nonlinear oscillations Nonparametric time series modeling Principal component analysis Reconstructing state spaces from experimental data Statistical methods in neuroscience Statistical parameter estimation Unsupervised clustering |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00123545 |
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Durstewitz, Daniel
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| Cham, : Springer, 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Compressed sensing and its applications : Second International MATHEON Conference 2015 / Holger Boche ... [et al.] editors
| Compressed sensing and its applications : Second International MATHEON Conference 2015 / Holger Boche ... [et al.] editors |
| Pubbl/distr/stampa | Cham, : Birkhäuser, 2017 |
| Descrizione fisica | xix, 388 p. : ill. ; 24 cm |
| Soggetto topico |
90C25 - Convex programming [MSC 2020]
68U10 - Computing methodologies for image processing [MSC 2020] 15B52 - Random matrices (algebraic aspects) [MSC 2020] 94A12 - Signal theory (characterization, reconstruction, filtering, etc.) [MSC 2020] 94A20 - Sampling theory in information and communication theory [MSC 2020] |
| Soggetto non controllato |
Compressed Sensing
Dimensionality reduction Fourier phase retrieval Hilbert spaces Information Theory Information and communication, circuits Matrix theory Random matrices Sparse approximation Sparse probability measures Sparse recovery Stochastic block model |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0124337 |
| Cham, : Birkhäuser, 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Compressed sensing and its applications : Second International MATHEON Conference 2015 / Holger Boche ... [et al.] editors
| Compressed sensing and its applications : Second International MATHEON Conference 2015 / Holger Boche ... [et al.] editors |
| Pubbl/distr/stampa | Cham, : Birkhäuser, 2017 |
| Descrizione fisica | xix, 388 p. : ill. ; 24 cm |
| Soggetto topico |
15B52 - Random matrices (algebraic aspects) [MSC 2020]
68U10 - Computing methodologies for image processing [MSC 2020] 90C25 - Convex programming [MSC 2020] 94A12 - Signal theory (characterization, reconstruction, filtering, etc.) [MSC 2020] 94A20 - Sampling theory in information and communication theory [MSC 2020] |
| Soggetto non controllato |
Compressed Sensing
Dimensionality reduction Fourier phase retrieval Hilbert spaces Information Theory Information and communication, circuits Matrix theory Random matrices Sparse approximation Sparse probability measures Sparse recovery Stochastic block model |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00124337 |
| Cham, : Birkhäuser, 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Dimensionality Reduction in Data Science / Max Garzon ... [et al.] editors
| Dimensionality Reduction in Data Science / Max Garzon ... [et al.] editors |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | xi, 265 p. : ill. ; 24 cm |
| Soggetto non controllato |
Classification/Prediction
Cross-validation DNA hybridization Data Visualization Data science platforms Deep learning/Backpropagation Dimensionality reduction Experimental control Explainable solutions Extreme Dimensionality reduction Geometric methods Independent component analysis Information-theoretic methods Machine learning Molecular Methods No-Free-Lunch (NFL) theorem Regression methods Semi/Unsupervised learning Statistical Methods Supervised learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0277281 |
| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Dimensionality Reduction in Data Science / Max Garzon ... [et al.] editors
| Dimensionality Reduction in Data Science / Max Garzon ... [et al.] editors |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | xi, 265 p. : ill. ; 24 cm |
| Soggetto topico |
00B15 - Collections of articles of miscellaneous specific interest [MSC 2020]
68-XX - Computer science [MSC 2020] 68T09 - Computational aspects of data analysis and big data [MSC 2020] |
| Soggetto non controllato |
Classification/Prediction
Cross-validation DNA hybridization Data Visualization Data science platforms Deep learning/Backpropagation Dimensionality reduction Experimental control Explainable solutions Extreme Dimensionality reduction Geometric methods Independent component analysis Information-theoretic methods Machine learning Molecular Methods No-Free-Lunch (NFL) theorem Regression methods Semi/Unsupervised learning Statistical Methods Supervised learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00277281 |
| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Euclidean Distance Geometry : an introduction / Leo Liberti, Carlile Lavor
| Euclidean Distance Geometry : an introduction / Leo Liberti, Carlile Lavor |
| Autore | Liberti, Leo |
| Pubbl/distr/stampa | Cham, : Springer, 2017 |
| Descrizione fisica | xiii, 133 p. : ill. ; 24 cm |
| Altri autori (Persone) | Lavor, Carlile |
| Soggetto topico | 51Kxx - Distance geometry [MSC 2020] |
| Soggetto non controllato |
Branch-and-Prune algorithm
Clock synchronization Complete graphs Convex Optimization Dimensionality reduction Discretizability Graph visualization Isomap K-laterative graphs Localization of sensor networks Mathematica Mathematical programming Multidimensional Scaling Unmanned underwater vehicles Vertex orders Weighted adjacency matrix |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0123996 |
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Liberti, Leo
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| Cham, : Springer, 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Euclidean Distance Geometry : an introduction / Leo Liberti, Carlile Lavor
| Euclidean Distance Geometry : an introduction / Leo Liberti, Carlile Lavor |
| Autore | Liberti, Leo |
| Pubbl/distr/stampa | Cham, : Springer, 2017 |
| Descrizione fisica | xiii, 133 p. : ill. ; 24 cm |
| Altri autori (Persone) | Lavor, Carlile |
| Soggetto topico | 51Kxx - Distance geometry [MSC 2020] |
| Soggetto non controllato |
Branch-and-Prune algorithm
Clock synchronization Complete graphs Convex Optimization Dimensionality reduction Discretizability Graph visualization Isomap K-laterative graphs Localization of sensor networks Mathematica Mathematical programming Multidimensional Scaling Unmanned underwater vehicles Vertex orders Weighted adjacency matrix |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00123996 |
|
Liberti, Leo
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||
| Cham, : Springer, 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Fundamentals of Data Analytics : With a View to Machine Learning / Rudolf Mathar ... [et al.]
| Fundamentals of Data Analytics : With a View to Machine Learning / Rudolf Mathar ... [et al.] |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | xi, 127 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
68T05 - Learning and adaptive systems in artificial intelligence [MSC 2020] 62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020] 62R07 - Statistical aspects of big data and data science [MSC 2020] |
| Soggetto non controllato |
Artificial Intelligence
Classification Clustering Data science Diffusion maps Dimensionality reduction Isomap Kernel methods Machine learning MapReduce Markov decision processes Matrix optimization and approximation Multidimensional Scaling Principal component analysis Spectral clustering Supervised machine learning Support Vector Machines Unsupervised machine learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0249280 |
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Fundamentals of Data Analytics : With a View to Machine Learning / Rudolf Mathar ... [et al.]
| Fundamentals of Data Analytics : With a View to Machine Learning / Rudolf Mathar ... [et al.] |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | xi, 127 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020] 62R07 - Statistical aspects of big data and data science [MSC 2020] 68T05 - Learning and adaptive systems in artificial intelligence [MSC 2020] |
| Soggetto non controllato |
Artificial Intelligence
Classification Clustering Data science Diffusion maps Dimensionality reduction Isomap Kernel methods Machine learning MapReduce Markov decision processes Matrix optimization and approximation Multidimensional Scaling Principal component analysis Spectral clustering Supervised machine learning Support Vector Machines Unsupervised machine learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00249280 |
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
