Sublinear Computation Paradigm : Algorithmic Revolution in the Big Data Era /

This open access book gives an overview of cutting-edge work on a new paradigm called the "sublinear computation paradigm," which was proposed in the large multiyear academic research project "Foundations of Innovative Algorithms for Big Data." That project ran from October 2014...

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Bibliographic Details
Corporate Author:	SpringerLink (Online service)
Other Authors:	Katoh, Naoki (Editor), Higashikawa, Yuya (Editor), Ito, Hiro (Editor), Nagao, Atsuki (Editor), Shibuya, Tetsuo (Editor), Sljoka, Adnan (Editor), Tanaka, Kazuyuki (Editor), Uno, Yushi (Editor)
Format:	eBook
Language:	English
Published:	Singapore : Springer Singapore : Imprint: Springer, 2022.
Edition:	1st ed. 2022.
Subjects:	Algorithms. Algorithm Analysis and Problem Complexity. Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Chapter 1: What is the Sublinear Computation Paradigm?
Chapter 2: Property Testing on Graphs and Games
Chapter 3: Constant-Time Algorithms for Continuous Optimization Problems
Chapter 4: Oracle-based Primal-Dual Algorithms for Packing and Covering Semidefinite Programs
Chapter 5: Almost Linear Time Algorithms for Some Problems on Dynamic Flow Networks
Chapter 6: Sublinear Data Structure
Chapter 7: Compression and Pattern Matching
Chapter 8: Orthogonal Range Search Data Structures
Chapter 9: Enhanced RAM Simulation in Succinct Space
Chapter 10: Review of Sublinear Modeling in Markov Random Fields by Statistical-Mechanical Informatics and Statistical Machine Learning Theory
Chapter 11: Empirical Bayes Method for Boltzmann Machines
Chapter 12: Dynamical analysis of quantum annealing
Chapter 13: Mean-field analysis of Sourlas codes with adiabatic reverse annealing
Chapter 14: Rigidity theory for protein function analysis and structural accuracy validations
Chapter 15: Optimization of Evacuating and Walking Home Routes from Osaka City with Big Road Network Data on Nankai Megathrust Earthquake
Chapter 16: Stream-based Lossless Data Compression.