„high-dimensional data analysis“

Suchergebnisse

256 Treffer

• Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXI – Special Issue on Data and Security Engineering
  Hameurlain, Abdelkader ; Küng, Josef ; Wagner, Roland ; Dang, Tran Khanh ; Thoai, Nam 2017 Springer Berlin Heidelberg
• Deep learning models for the analysis of high-dimensional survival data with time-varying covariates while handling missing data
  Ogutu, Sarah ; Mohammed, Mohanad ; Mwambi, Henry
• A Deep Shotgun Method for Solving High-Dimensional Parabolic Partial Differential Equations
  Xu, Wenjun ; Zhang, Wenzhong
• Advanced real-time monitoring techniques for high-dimensional data streams in industrial two-sample analysis
  Mahmood, Tahir ; Riaz, Muhammad ; Abbas, Nasir ; Ahmed, Fuhad
• Sparse proteomics analysis – a compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data
  Conrad, Tim O. F. ; Genzel, Martin ; Cvetković, Nada ; Wulkow, Niklas ; Leichtle, Alexander ; Vybiral, Jan ; Kutyniok, Gitta ; Schütte, Christof 2017 Universität Augsburg
• Stochastic Models, Statistics and Their Applications – Wrocław, Poland, February 2015
  Steland, Ansgar ; Rafajłowicz, Ewaryst ; Szajowski, Krzysztof 2015 Springer International Publishing
• Topics in Applied Statistics – 2012 Symposium of the International Chinese Statistical Association
  Hu, Mingxiu ; Liu, Yi ; Jianchang, Lin 2013 Springer New York
• Topics in the statistical analysis of rare events and high-dimensional data sets
  Stenz, Hartmut Jacob 2023 Publikationsserver ibib
• Sparse Proteomics Analysis – a compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data
  Conrad, Tim O. F. ; Genzel, Martin ; Cvetković, Nada ; Wulkow, Niklas ; Leichtle, Alexander ; Vybiral, Jan ; Kutyniok, Gitta ; Schütte, Christof 2019 Technische Universität Berlin
• Sparse Proteomics Analysis – a compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data
  Conrad, Tim O. F. ; Genzel, Martin ; Cvetković, Nada ; Wulkow, Niklas ; Leichtle, Alexander ; Vybiral, Jan ; Kutyniok, Gitta ; Schütte, Christof
• Clustering High--Dimensional Data – First International Workshop, CHDD 2012, Naples, Italy, May 15, 2012, Revised Selected Papers
  Masulli, Francesco ; Petrosino, Alfredo ; Rovetta, Stefano 2015 Springer Berlin Heidelberg
• Time Series Analysis and Forecasting – Selected Contributions from the ITISE Conference
  Rojas, Ignacio ; Pomares, Héctor 2016 Springer International Publishing
• Transactions on Large-Scale Data- and Knowledge-Centered Systems XXVIII – Special Issue on Database- and Expert-Systems Applications
  2016 Springer International Publishing
• Transactions on Large-Scale Data- and Knowledge-Centered Systems XXVII – Special Issue on Big Data for Complex Urban Systems
  Hameurlain, Abdelkader ; Küng, Josef ; Wagner, Roland ; Chen, Qimin 2016 Springer Berlin Heidelberg
• New Advances in Statistics and Data Science
  Chen, Ding-Geng ; Jin, Zhezhen ; Li, Gang ; Li, Yi ; Liu, Aiyi ; Zhao, Yichuan 2017 Springer International Publishing
• Data Science – Innovative Developments in Data Analysis and Clustering
  Palumbo, Francesco ; Montanari, Angela ; Vichi, Maurizio 2017 Springer International Publishing
• Sparse Grids and Applications - Miami 2016
  Garcke, Jochen ; Pflüger, Dirk ; Webster, Clayton G. ; Zhang, Guannan 2018 Springer International Publishing
• Big and Complex Data Analysis – Methodologies and Applications
  Ahmed, Syed E. 2017 Springer International Publishing
• Statistical Analysis for High-Dimensional Data – The Abel Symposium 2014
  Frigessi, Arnoldo ; Bühlmann, Peter ; Glad, Ingrid ; Langaas, Mette ; Richardson, Sylvia ; Vannucci, Marina 2016 Springer International Publishing
• CRAmed: a conditional randomization test for high-dimensional mediation analysis in sparse microbiome data
  Liu, Tiantian ; Xu, Xiangnan ; Wang, Tao ; Xu, Peirong 2025 Humboldt-Universität zu Berlin