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245 1 0 _aBraverman Readings in Machine Learning. Key Ideas from Inception to Current State
_h[electronic resource] :
_bInternational Conference Commemorating the 40th Anniversary of Emmanuil Braverman's Decease, Boston, MA, USA, April 28-30, 2017, Invited Talks /
_cedited by Lev Rozonoer, Boris Mirkin, Ilya Muchnik.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXII, 353 p. 65 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
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490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v11100
505 0 _aPotential Functions for Signals and Symbolic Sequences -- Braverman's Spectrum and Matrix Diagonalization versus iK-Means: A Unified Framework for Clustering -- Compactness Hypothesis, Potential Functions, and Rectifying Linear Space in Machine Learning -- Conformal Predictive Distributions with Kernels -- On the Concept of Compositional Complexity -- On the Choice of a Kernel Function in Symmetric Spaces -- Causality Modeling and Statistical Generative Mechanisms -- One-Class Semi-Supervised Learning -- Prediction of Drug Efficiency by Transferring Gene Expression Data from Cell Lines to Cancer Patients -- On One Approach to Robot Motion Planning -- Geometrical Insights for Implicit Generative Modeling -- Deep Learning in the Natural Sciences: Applications to Physics -- From Reinforcement Learning to Deep Reinforcement Learning: An Overview -- A Man of Unlimited Capabilities -- Braverman and His Theory of Disequilibrium Economics -- Misha Braverman: My Mentor and My Model -- List of Braverman's papers published in the "Avtomatika itelemekhanika" journal, Moscow, Russia, and translated into English as "Automation and Remote Control" journal.
520 _aThis state-of-the-art survey is dedicated to the memory of Emmanuil Markovich Braverman (1931-1977), a pioneer in developing the machine learning theory. The 12 revised full papers and 4 short papers included in this volume were presented at the conference "Braverman Readings in Machine Learning: Key Ideas from Inception to Current State" held in Boston, MA, USA, in April 2017, commemorating the 40th anniversary of Emmanuil Braverman's decease. The papers present an overview of some of Braverman's ideas and approaches. The collection is divided in three parts. The first part bridges the past and the present. Its main contents relate to the concept of kernel function and its application to signal and image analysis as well as clustering. The second part presents a set of extensions of Braverman's work to issues of current interest both in theory and applications of machine learning.The third part includes short essays by a friend, a student, and a colleague.
650 0 _aArtificial intelligence.
_93407
650 0 _aAlgorithms.
_93390
650 0 _aComputer science
_xMathematics.
_93866
650 0 _aMathematical statistics.
_99597
650 0 _aData mining.
_93907
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aAlgorithms.
_93390
650 2 4 _aProbability and Statistics in Computer Science.
_931857
650 2 4 _aData Mining and Knowledge Discovery.
_9166686
700 1 _aRozonoer, Lev.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
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700 1 _aMirkin, Boris.
_eeditor.
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700 1 _aMuchnik, Ilya.
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710 2 _aSpringerLink (Online service)
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
_z9783319994932
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v11100
_9166691
856 4 0 _uhttps://doi.org/10.1007/978-3-319-99492-5
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