Cantitate/Preț
Produs
Total produse
Vezi coșul
Braverman Readings in Machine Learning. Key Ideas from Inception to Current State: International Conference Commemorating the 40th Anniversary of Emmanuil Braverman's Decease, Boston, MA, USA, April 28-30, 2017, Invited Talks de Lev Rozonoer

Braverman Readings in Machine Learning. Key Ideas from Inception to Current State: International Conference Commemorating the 40th Anniversary of Emmanuil Braverman's Decease, Boston, MA, USA, April 28-30, 2017, Invited Talks: Lecture Notes in Computer Science, cartea 11100

Editat de Lev Rozonoer, Boris Mirkin, Ilya Muchnik
en Limba Engleză Paperback – 24 aug 2018
This state-of-the-art survey is dedicated to the memory of Emmanuil Markovich Braverman (1931-1977), a pioneer in developing 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 and covers 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 essaysby a friend, a student, and a colleague.


Citește tot Restrânge

Din seria Lecture Notes in Computer Science

Preț: 32631 lei

Preț vechi: 40788 lei
-20% Nou

Puncte Express: 489
Preț estimativ în valută:
6246€ • 6509$ • 5199£

Carte tipărită la comandă

Livrare economică 06-20 ianuarie 25

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă
Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783319994918
ISBN-10: 3319994913
Pagini: 353
Ilustrații: XII, 353 p. 65 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.51 kg
Ediția:1st ed. 2018
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence

Locul publicării:Cham, Switzerland

Cuprins

Potential 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.

Notă biografică

Lev Rozonoer, West Newton, MA, USA;
Boris Mirkin, National Research University Higher School of Economics, Moscow, Russian Federation;
Ilya Muchnik, Rutgers University, Piscataway, NJ, USA.

Textul de pe ultima copertă

This 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.

Caracteristici

Oriented at students, developers and practitioners in machine learning and data analysis Provides useful insights into the role of parameters Interesting to historians