Braverman Readings in Machine Learning. Key Ideas from Inception to Current State - Lecture Notes in Computer Science
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Published By Springer International Publishing

9783319994918, 9783319994925

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On the Choice of a Kernel Function in Symmetric Spaces

Braverman Readings in Machine Learning. Key Ideas from Inception to Current State - Lecture Notes in Computer Science ◽

10.1007/978-3-319-99492-5_6 ◽

2018 ◽

pp. 128-147

Author(s):

M. A. Aizerman ◽

E. M. Braverman ◽

Lev I. Rozonoer

Keyword(s):

Kernel Function ◽

Symmetric Spaces

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On One Approach to Robot Motion Planning

Braverman Readings in Machine Learning. Key Ideas from Inception to Current State - Lecture Notes in Computer Science ◽

10.1007/978-3-319-99492-5_10 ◽

2018 ◽

pp. 213-228

Author(s):

Vladimir Lumelsky

Keyword(s):

Motion Planning ◽

Robot Motion ◽

Robot Motion Planning

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Conformal Predictive Distributions with Kernels

Braverman Readings in Machine Learning. Key Ideas from Inception to Current State - Lecture Notes in Computer Science ◽

10.1007/978-3-319-99492-5_4 ◽

2018 ◽

pp. 103-121 ◽

Cited By ~ 1

Author(s):

Vladimir Vovk ◽

Ilia Nouretdinov ◽

Valery Manokhin ◽

Alex Gammerman

Keyword(s):

Predictive Distributions

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From Reinforcement Learning to Deep Reinforcement Learning: An Overview

Braverman Readings in Machine Learning. Key Ideas from Inception to Current State - Lecture Notes in Computer Science ◽

10.1007/978-3-319-99492-5_13 ◽

2018 ◽

pp. 298-328

Author(s):

Forest Agostinelli ◽

Guillaume Hocquet ◽

Sameer Singh ◽

Pierre Baldi

Keyword(s):

Reinforcement Learning

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Deep Learning in the Natural Sciences: Applications to Physics

Braverman Readings in Machine Learning. Key Ideas from Inception to Current State - Lecture Notes in Computer Science ◽

10.1007/978-3-319-99492-5_12 ◽

2018 ◽

pp. 269-297 ◽

Cited By ~ 1

Author(s):

Peter Sadowski ◽

Pierre Baldi

Keyword(s):

Deep Learning ◽

Natural Sciences

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Potential Functions for Signals and Symbolic Sequences

Braverman Readings in Machine Learning. Key Ideas from Inception to Current State - Lecture Notes in Computer Science ◽

10.1007/978-3-319-99492-5_1 ◽

2018 ◽

pp. 3-31

Author(s):

Valentina Sulimova ◽

Vadim Mottl

Keyword(s):

Potential Functions ◽

Symbolic Sequences

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Misha Braverman: My Mentor and My Model

Braverman Readings in Machine Learning. Key Ideas from Inception to Current State - Lecture Notes in Computer Science ◽

10.1007/978-3-319-99492-5_16 ◽

2018 ◽

pp. 341-348

Author(s):

Boris Mirkin

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Prediction of Drug Efficiency by Transferring Gene Expression Data from Cell Lines to Cancer Patients

Braverman Readings in Machine Learning. Key Ideas from Inception to Current State - Lecture Notes in Computer Science ◽

10.1007/978-3-319-99492-5_9 ◽

2018 ◽

pp. 201-212 ◽

Cited By ~ 6

Author(s):

Nicolas Borisov ◽

Victor Tkachev ◽

Anton Buzdin ◽

Ilya Muchnik

Keyword(s):

Gene Expression ◽

Cancer Patients ◽

Cell Lines ◽

Gene Expression Data ◽

Expression Data ◽

Drug Efficiency

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Correction to: Braverman and His Theory of Disequilibrium Economics

Braverman Readings in Machine Learning. Key Ideas from Inception to Current State - Lecture Notes in Computer Science ◽

10.1007/978-3-319-99492-5_18 ◽

2018 ◽

pp. E1-E1

Author(s):

Mark Levin

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Causality Modeling and Statistical Generative Mechanisms

Braverman Readings in Machine Learning. Key Ideas from Inception to Current State - Lecture Notes in Computer Science ◽

10.1007/978-3-319-99492-5_7 ◽

2018 ◽

pp. 148-186 ◽

Cited By ~ 3

Author(s):

Igor Mandel

Keyword(s):

Generative Mechanisms

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Braverman Readings in Machine Learning. Key Ideas from Inception to Current State - Lecture Notes in Computer ScienceLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

On the Choice of a Kernel Function in Symmetric Spaces

On One Approach to Robot Motion Planning

Conformal Predictive Distributions with Kernels

From Reinforcement Learning to Deep Reinforcement Learning: An Overview

Deep Learning in the Natural Sciences: Applications to Physics

Potential Functions for Signals and Symbolic Sequences

Misha Braverman: My Mentor and My Model

Prediction of Drug Efficiency by Transferring Gene Expression Data from Cell Lines to Cancer Patients

Correction to: Braverman and His Theory of Disequilibrium Economics

Causality Modeling and Statistical Generative Mechanisms

Braverman Readings in Machine Learning. Key Ideas from Inception to Current State - Lecture Notes in Computer Science
Latest Publications