Applied Machine Learning
Latest Publications

TOTAL DOCUMENTS

19

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Published By Springer International Publishing

9783030181130, 9783030181147

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Low Rank Approximations

Applied Machine Learning ◽

10.1007/978-3-030-18114-7_6 ◽

2019 ◽

pp. 117-138

Author(s):

David Forsyth

Keyword(s):

Low Rank ◽

Low Rank Approximations

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High Dimensional Data

Applied Machine Learning ◽

10.1007/978-3-030-18114-7_4 ◽

2019 ◽

pp. 69-91

Author(s):

David Forsyth

Keyword(s):

High Dimensional Data ◽

High Dimensional

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Hidden Markov Models

Applied Machine Learning ◽

10.1007/978-3-030-18114-7_13 ◽

2019 ◽

pp. 305-332

Author(s):

David Forsyth

Keyword(s):

Hidden Markov Models ◽

Markov Models ◽

Hidden Markov

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Clustering Using Probability Models

Applied Machine Learning ◽

10.1007/978-3-030-18114-7_9 ◽

2019 ◽

pp. 183-202

Author(s):

David Forsyth

Keyword(s):

Probability Models

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Small Codes for Big Signals

Applied Machine Learning ◽

10.1007/978-3-030-18114-7_19 ◽

2019 ◽

pp. 455-478

Author(s):

David Forsyth

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Simple Neural Networks

Applied Machine Learning ◽

10.1007/978-3-030-18114-7_16 ◽

2019 ◽

pp. 367-398

Author(s):

David Forsyth

Keyword(s):

Neural Networks

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Learning Sequence Models Discriminatively

Applied Machine Learning ◽

10.1007/978-3-030-18114-7_14 ◽

2019 ◽

pp. 333-350

Author(s):

David Forsyth

Keyword(s):

Learning Sequence

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Regression

Applied Machine Learning ◽

10.1007/978-3-030-18114-7_10 ◽

2019 ◽

pp. 205-244

Author(s):

David Forsyth

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SVMs and Random Forests

Applied Machine Learning ◽

10.1007/978-3-030-18114-7_2 ◽

2019 ◽

pp. 21-48

Author(s):

David Forsyth

Keyword(s):

Random Forests

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Regression: Choosing and Managing Models

Applied Machine Learning ◽

10.1007/978-3-030-18114-7_11 ◽

2019 ◽

pp. 245-274

Author(s):

David Forsyth

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