Statistical Learning and Data Sciences - Lecture Notes in Computer Science
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Published By Springer International Publishing

9783319170909, 9783319170916

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Adaptive Design of Experiments Based on Gaussian Processes

Statistical Learning and Data Sciences - Lecture Notes in Computer Science ◽

10.1007/978-3-319-17091-6_7 ◽

2015 ◽

pp. 116-125 ◽

Author(s):

Evgeny Burnaev ◽

Maxim Panov

Keyword(s):

Design Of Experiments ◽

Gaussian Processes ◽

Adaptive Design ◽

Adaptive Design Of Experiments

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Aggregation of Adaptive Forecasting Algorithms Under Asymmetric Loss Function

Statistical Learning and Data Sciences - Lecture Notes in Computer Science ◽

10.1007/978-3-319-17091-6_9 ◽

2015 ◽

pp. 137-146 ◽

Author(s):

Alexey Romanenko

Keyword(s):

Loss Function ◽

Asymmetric Loss ◽

Asymmetric Loss Function

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Confinement Regime Identification Using Artificial Intelligence Methods

Statistical Learning and Data Sciences - Lecture Notes in Computer Science ◽

10.1007/978-3-319-17091-6_28 ◽

2015 ◽

pp. 337-346

Author(s):

G. A. Rattá ◽

J. Vega

Keyword(s):

Artificial Intelligence ◽

Artificial Intelligence Methods

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Recursive SVM Based on TEDA

Statistical Learning and Data Sciences - Lecture Notes in Computer Science ◽

10.1007/978-3-319-17091-6_11 ◽

2015 ◽

pp. 156-168 ◽

Author(s):

Dmitry Kangin ◽

Plamen Angelov

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Model Selection Using Efficiency of Conformal Predictors

Statistical Learning and Data Sciences - Lecture Notes in Computer Science ◽

10.1007/978-3-319-17091-6_24 ◽

2015 ◽

pp. 291-300

Author(s):

Ritvik Jaiswal ◽

Vineeth N. Balasubramanian

Keyword(s):

Model Selection ◽

Conformal Predictors

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Computationally Efficient Five-Class Image Classifier Based on Venn Predictors

Statistical Learning and Data Sciences - Lecture Notes in Computer Science ◽

10.1007/978-3-319-17091-6_31 ◽

2015 ◽

pp. 366-375 ◽

Author(s):

J. Vega ◽

S. Dormido-Canto ◽

F. Martínez ◽

I. Pastor ◽

M. C. Rodríguez

Keyword(s):

Computationally Efficient

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Feature Mapping Through Maximization of the Atomic Interclass Distances

Statistical Learning and Data Sciences - Lecture Notes in Computer Science ◽

10.1007/978-3-319-17091-6_3 ◽

2015 ◽

pp. 75-85

Author(s):

Savvas Karatsiolis ◽

Christos N. Schizas

Keyword(s):

Feature Mapping

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How to Handle Error Bars in Symbolic Regression for Data Mining in Scientific Applications

Statistical Learning and Data Sciences - Lecture Notes in Computer Science ◽

10.1007/978-3-319-17091-6_29 ◽

2015 ◽

pp. 347-355 ◽

Author(s):

A. Murari ◽

E. Peluso ◽

M. Gelfusa ◽

M. Lungaroni ◽

P. Gaudio

Keyword(s):

Data Mining ◽

Symbolic Regression ◽

Scientific Applications ◽

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Lattice-Theoretic Approach to Version Spaces in Qualitative Decision Making

Statistical Learning and Data Sciences - Lecture Notes in Computer Science ◽

10.1007/978-3-319-17091-6_18 ◽

2015 ◽

pp. 234-238

Author(s):

Miguel Couceiro ◽

Tamás Waldhauser

Keyword(s):

Decision Making ◽

Theoretic Approach ◽

Version Spaces ◽

Qualitative Decision

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Visualization and Analysis of Multiple Time Series by Beanplot PCA

Statistical Learning and Data Sciences - Lecture Notes in Computer Science ◽

10.1007/978-3-319-17091-6_10 ◽

2015 ◽

pp. 147-155

Author(s):

Carlo Drago ◽

Carlo Natale Lauro ◽

Germana Scepi

Keyword(s):

Time Series ◽

Multiple Time ◽

Multiple Time Series

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