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Approximation Theory and Algorithms for Data Analysis

algorithms for data analysis plays an important role. The following topics are covered: * least-squares approximation and regularization methods;

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Foundations of Applied Mathematics, Volume 2

of algorithms for mathematicians and data science students; probability and its applications; the theory and applications of approximation, including;

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Approximation and Online Algorithms

, echanism design, network design, packing and covering, paradigms for design and analysis of approximation and online algorithms, parameterized;

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Approximation and Online Algorithms

; inapproximability results; network design; packing and covering; paradigms for the design and analysis of approximation and online algorithms; parameterized;

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Approximation and Online Algorithms

; inapproximability results; network design; packing and covering; paradigms for the design and analysis of approximation and online algorithms; parameterized;

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Approximate Iterative Algorithms

in functional analysis and probability theory. Extensive applications to Markov decision processes are presented. This volume is intended for;

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Approximate Iterative Algorithms

in functional analysis and probability theory. Extensive applications to Markov decision processes are presented. This volume is intended for;

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Numerical Computations: Theory and Algorithms

of these special sessions: approximation: methods, algorithms, and applications; computational methods for data analysis; first order methods;

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Foundations of Computational Intelligence Volume 5

Foundations of Computational Intelligence Volume 5: Function Approximation and Classification Approximation theory is that area of analysis;

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Combinatorial Algorithms

of 90 submissions. The topics of the papers include algorithms and data structures (including sequential, parallel, distributed, approximation;

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Numerical Fourier Analysis

This book offers a unified presentation of Fourier theory and corresponding algorithms emerging from new developments in function;

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LATIN 2018: Theoretical Informatics

game theory, etc.), analytic combinatorics and analysis of algorithms, automata theory and formal languages, coding theory and data compression;

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Guide to Graph Algorithms

comparative analysis of sequential, parallel and distributed graph algorithms - including algorithms for big data - and an investigation into the;

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Sparse Approximation with Bases

approximation. Taking into account the theoretical and practical demand for this kind of theory, the book systematically elaborates a theoretical;

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Approximation and Online Algorithms

analysis, network design, packing and covering, paradigms for design and analysis of approximation and online algorithms, randomization techniques;

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Approximation and Online Algorithms

design, packing and covering, paradigms for design and analysis of approximation and online algorithms, randomization techniques, real-world;

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Nodal Discontinuous Galerkin Methods: Algorithms, Analysis, and Applications

results from approximation theory, convergence theory for numerical PDE's, and orthogonal polynomials. Through embedded Matlab codes, coverage;

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Computing and Combinatorics

various submissions. The papers cover various topics including: Theory and Algorithms; Parameterized Complexity and Algorithms; Database and Data;

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Computer Science - Theory and Applications

broad range of topics, such as: algorithms and data structures; computational complexity, including hardness of approximation and parameterized;

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Data Streams

embeddings, pseudo-random computations, sparse approximation theory and communication complexity. The applications for this scenario include IP;

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Constrained Clustering

in Algorithms, Theory, and Applications presents an extensive collection of the latest innovations in clustering data analysis methods that use;

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Greedy Approximation

hot topics in numerical mathematics: learning theory and compressed sensing. Nonlinear approximation is becoming increasingly important;

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Approximation and Online Algorithms

, online algorithms, scheduling, algorithmic game theory, and approximation algorithms.;

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Computational Mathematics and Variational Analysis

, operations research, game theory, differential equations, functional analysis, operator theory, approximation theory, numerical analysis, asymptotic;

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Stochastic Approximation and Recursive Algorithms and Applications

This book presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both;

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Stochastic Approximation and Recursive Algorithms and Applications

This book presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both;

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The Best Approximation Method in Computational Mechanics

, despite the vast quantities of synthetic data there is still some doubt concerning the validity and accuracy of these approximations. This;

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