Search Results - "Multivariate function approximation"

Constructing Embedded Lattice-Based Algorithms for Multivariate Function Approximation with a Composite Number of Points

Authors: Kuo, Frances Y. Mo, Weiwen Nuyens, Dirk

Source: Constructive Approximation. 61:81-113

Subject Terms: 65D15, 65T40, FOS: Mathematics, Mathematics - Numerical Analysis, Numerical Analysis (math.NA), 0101 mathematics, 01 natural sciences

Access URL: http://arxiv.org/abs/2209.01002
https://lirias.kuleuven.be/handle/20.500.12942/734999
https://doi.org/10.48550/arxiv.2209.01002

Tensor-based multivariate function approximation: methods benchmarking and comparison

Authors: Antoulas, Athanasios C. Gosea, Ion Victor Poussot-Vassal, Charles et al.

Subject Terms: Computational Engineering, Finance, and Science (cs.CE), Software Engineering (cs.SE), FOS: Computer and information sciences, Computer Science - Software Engineering, FOS: Mathematics, Mathematics - Numerical Analysis, Numerical Analysis (math.NA), Computer Science - Computational Engineering, Finance, and Science, 93A15, 93A30, 93B11, 93B15, 93C05, 93C80

Access URL: http://arxiv.org/abs/2506.04791

An Adaptive Sampling and Domain Learning Strategy for Multivariate Function Approximation on Unknown Domains

Authors: Ben Adcock Juan M. Cardenas Nick Dexter

Source: SIAM Journal on Scientific Computing. 45:A200-A225

Subject Terms: FOS: Mathematics, Mathematics - Numerical Analysis, Numerical Analysis (math.NA), 0101 mathematics, 01 natural sciences

Access URL: http://arxiv.org/abs/2202.00144

Application of Feedforward Neura Networks in Multivariate Function Approximation

Source: Statistics and Application. :1048-1059

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 0101 mathematics, 01 natural sciences

Near-Optimal Sampling Strategies for Multivariate Function Approximation on General Domains

Authors: Juan M. Cardenas Ben Adcock

Source: SIAM Journal on Mathematics of Data Science. 2:607-630

Subject Terms: FOS: Mathematics, Mathematics - Numerical Analysis, Numerical Analysis (math.NA), 0101 mathematics, 01 natural sciences

Access URL: https://epubs.siam.org/doi/pdf/10.1137/19M1279459
http://arxiv.org/abs/1908.01249
https://epubs.siam.org/doi/pdf/10.1137/19M1279459
https://dblp.uni-trier.de/db/journals/corr/corr1908.html#abs-1908-01249
https://epubs.siam.org/doi/abs/10.1137/19M1279459

Constructing Embedded Lattice-based Algorithms for Multivariate Function Approximation with a Composite Number of Points

Authors: Kuo, Frances Y. Mo, Weiwen Nuyens, Dirk

Index Terms: Mathematics - Numerical Analysis, 65D15, 65T40, text

URL: http://arxiv.org/abs/2209.01002

An Adaptive sampling and domain learning strategy for multivariate function approximation on unknown domains

Authors: Adcock, Ben Cardenas, Juan M. Dexter, Nick

Index Terms: Mathematics - Numerical Analysis, text

URL: http://arxiv.org/abs/2202.00144

A Randomized Algorithm for Multivariate Function Approximation

Authors: Yeonjong Shin Dongbin Xiu

Source: SIAM Journal on Scientific Computing. 39:A983-A1002

Subject Terms: 0103 physical sciences, 0101 mathematics, 01 natural sciences

Access URL: https://epubs.siam.org/doi/abs/10.1137/16M1075193
http://dblp.uni-trier.de/db/journals/siamsc/siamsc39.html#ShinX17
https://dblp.uni-trier.de/db/journals/siamsc/siamsc39.html#ShinX17
https://locus.siam.org/doi/abs/10.1137/16M1075193

Correcting Data Corruption Errors for Multivariate Function Approximation

Authors: Yeonjong Shin Dongbin Xiu

Source: SIAM Journal on Scientific Computing. 38:A2492-A2511

Subject Terms: 0101 mathematics, 01 natural sciences

A novel piecewise multivariate function approximation method via universal matrix representation

Authors: Süha Tuna Burcu Tunga

Source: Journal of Mathematical Chemistry. 51:1784-1801

Subject Terms: 0103 physical sciences, 0101 mathematics, 01 natural sciences

Access URL: https://link.springer.com/article/10.1007/s10910-013-0179-y
https://link.springer.com/content/pdf/10.1007%2Fs10910-013-0179-y.pdf

Near-optimal sampling strategies for multivariate function approximation on general domains

Authors: Adcock, Ben Cardenas, Juan M.

Index Terms: Mathematics - Numerical Analysis, text

URL: http://arxiv.org/abs/1908.01249

A constructive method for multivariate function approximation by multilayer perceptrons

Authors: Shlomo Geva Joaquin Sitte

Source: IEEE Transactions on Neural Networks. 3:621-624

Subject Terms: 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://pubmed.ncbi.nlm.nih.gov/18276462

Constructing Embedded Lattice-Based Algorithms for Multivariate Function Approximation with a Composite Number of Points.

Authors: Kuo, Frances Y. Mo, Weiwen Nuyens, Dirk

Source: Constructive Approximation; Feb2025, Vol. 61 Issue 1, p81-113, 33p

Subject Terms: COMPOSITE numbers, PRIME numbers, COMPOSITE construction, APPROXIMATION error, SPLINES

Smooting additive splines for multivariate function approximation

Authors: Genç, Cüneyt Argun Alpaydın, Ahmet İbrahim Ethem Diğer

Contributors: Genç, Cüneyt Argun Alpaydın, Ahmet İbrahim Ethem Diğer

Subject Terms: Spline, Computer Engineering and Computer Science and Control, Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrol

File Description: application/pdf

Access URL: https://acikbilim.yok.gov.tr/handle/20.500.12812/81157

Mathematical Foundations of Symmetrized Hyperbolic Tangent Activation in Neural Networks

Authors: Santos, Rômulo Damasclin Chaves dos orcid:0000-0002-9482-

Subject Terms: Neural Networks, Symmetrized Hyperbolic Tangent, Multivariate Function Approximation, Robustness and Convergence

Relation: https://zenodo.org/records/14868074; oai:zenodo.org:14868074; https://doi.org/10.5281/zenodo.14868074

Availability: https://doi.org/10.5281/zenodo.14868074
https://zenodo.org/records/14868074

Extending Universal Approximation to Fractional Function Spaces via Neural Network Operators

Authors: Santos, Rômulo Damasclin Chaves dos orcid:0000-0002-9482-

Subject Terms: Neural Network Operators, Stochastic Approximation, Fractional Calculus in Machine Learning, Multivariate Function Approximation

Relation: https://zenodo.org/records/14765634; oai:zenodo.org:14765634; https://doi.org/10.5281/zenodo.14765634

Availability: https://doi.org/10.5281/zenodo.14765634
https://zenodo.org/records/14765634

AN ADAPTIVE SAMPLING AND DOMAIN LEARNING STRATEGY FOR MULTIVARIATE FUNCTION APPROXIMATION ON UNKNOWN DOMAINS.

Authors: ADCOCK, BEN CARDENAS, JUAN M. DEXTER, NICK

Source: SIAM Journal on Scientific Computing; 2023, Vol. 45 Issue 1, pA200-A225, 26p

Subject Terms: LEARNING strategies, SAMPLING (Process), LEAST squares, SMOOTHNESS of functions, POLYNOMIAL chaos, POLYNOMIAL approximation

Multivariate function approximation using sparse grids and High Dimensional Model Representation – a comparison

Authors: Baran, Mateusz

Source: Technical Transactions

Availability: http://data.europeana.eu/aggregation/europeana/0940430/_nn30dwk
http://data.europeana.eu/item/0940430/_nn30dwk

IMPLEMENTATION OF OPTIMIZED ADAPTIVE CONTROL FUNCTIONS - A PROBLEM IN MULTIVARIATE FUNCTION APPROXIMATION

Authors: Richard Vance

Source: Astrodynamics Conference.

Access URL: https://arc.aiaa.org/doi/10.2514/6.1963-417
https://ntrs.nasa.gov/search.jsp?R=19630024544
https://repository.exst.jaxa.jp/dspace/handle/a-is/498089

Networks of exponential neurons for multivariate function approximation

Authors: Shlomo Geva Joaquin Sitte

Source: [Proceedings] 1991 IEEE International Joint Conference on Neural Networks. :2305-2310 vol.3

Access URL: http://ieeexplore.ieee.org/document/170732/
https://ieeexplore.ieee.org/document/170732/