Works Published in 2017
Displaying works 1 - 20 of 199 in total
Sorted by most recent date added to the index first, which may not be the same as publication date order.
2017 journal article
Sparse Approximation using $\ell_1-\ell_2$ Minimization and Its Application to Stochastic Collocation
SIAM Journal on Scientific Computing, 39(1), A229–A254.
TL;DR:
Theoretical estimates regarding its recoverability for both sparse and nonsparse signals are presented and the recoverability of both the standard $\ell_1-\ell_2$ minimization and Chebyshev weighted versions are studied.
(via Semantic Scholar)
Source: ORCID
Added: January 24, 2024
2017 journal article
A Randomized Tensor Quadrature Method for High Dimensional Polynomial Approximation
SIAM Journal on Scientific Computing, 39(5), A1811–A1833.
TL;DR:
By using a new randomized algorithm and taking advantage of the tensor structure of the grids, a highly efficient algorithm can be constructed that can be lower than the standard methods, when applicable, such as least squares.
(via Semantic Scholar)
Source: ORCID
Added: January 24, 2024
2017 journal article
A Randomized Algorithm for Multivariate Function Approximation
SIAM Journal on Scientific Computing, 39(3), A983–A1002.
TL;DR:
This paper demonstrates that by conducting the approximation randomly one sample at a time the RK method converges, and establishes the optimal sampling probability measure to achieve the optimal rate of convergence.
(via Semantic Scholar)
Source: ORCID
Added: January 24, 2024
2017 report
Hierarchical Matrices and Low-Rank Methods for Extreme-Scale Solvers.
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Sandia ….
Source: ORCID
Added: November 1, 2023
2017 report
A Parallel Hierarchical Low-Rank Solver for General Sparse Matrices.
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).
Source: ORCID
Added: November 1, 2023
2017 report
A Hierarchical Low-Rank Solver for Large Sparse Linear Systems.
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).
Source: ORCID
Added: November 1, 2023
2017 journal article
Numerical Modeling of the Hydrodynamic Loads Applied on the «BREST-300» Reactor Steam Generator Tubes during a Primary-to-Secondary Leak Accident
Vestnik MEI, (3), 33–40.
Contributors: A. Iskhakov*
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy
(OpenAlex)
Source: ORCID
Added: September 5, 2023
2017 article
Effective $l^2$ decoupling for the parabola
(2017, November 3).
Source: ORCID
Added: August 23, 2023
2017 thesis
Thin films with non-conservative effects
(PhD Dissertation). Duke University.
Source: NC State University Libraries
Added: May 23, 2023
2017 journal article
Global existence of solutions to a tear film model with locally elevated evaporation rates
Physica D: Nonlinear Phenomena, 350, 13–25.
Contributors: Y. Gao *, H. Ji* , J. Liu * & T. Witelski *
TL;DR:
Analysis of a generalized thin film model proposed by Peng et al. (2014) for break-up of tear films on human eyes analytically proves the global existence of solutions to this model with mobility exponents in several different ranges and presents numerical simulations in agreement with the analytic results.
(via Semantic Scholar)
manuscript.elsevier.com (publisher PDF)
Source: ORCID
Added: May 18, 2023
2017 journal article
Finite-time thin film rupture driven by modified evaporative loss
Physica D: Nonlinear Phenomena, 342, 1–15.
Contributors: H. Ji* & T. Witelski *
Source: ORCID
Added: May 18, 2023
2017 journal article
Virtualization Map for the Littelmann Path Model
Transformation Groups, 23(4), 1045–1061.
Sources: Crossref, NC State University Libraries
Added: March 31, 2023
2017 journal article
Perturbation Analysis for Investment Portfolios Under Partial Information with Expert Opinions
SIAM Journal on Control and Optimization, 55(3), 1534–1566.
author keywords: filtering; control; Hamilton-Jacobi-Bellman equation; portfolio optimization; partial information; expert opinions
Sources: ORCID, Crossref, NC State University Libraries
Added: January 13, 2023
2017 journal article
Dimension Reduction in Statistical Estimation of Partially Observed Multiscale Processes
SIAM/ASA Journal on Uncertainty Quantification, 5(1), 1220–1247.
author keywords: data assimilation; filtering; parameter estimation; homogenization; multiscale diffusions,dimension reduction
TL;DR:
It is established for a very general class of test functions that the filter of the original model converges to a filter of reduced dimension, which allows to learn the unknown parameters of interest while working in lower dimensions, as opposed to working with the original high dimensional system.
(via Semantic Scholar)
Sources: ORCID, Crossref, NC State University Libraries
Added: January 13, 2023
2017 book
Convex Analysis and Monotone Operator Theory in Hilbert Spaces
In CMS Books in Mathematics.
TL;DR:
This book provides a largely self-contained account of the main results of convex analysis and optimization in Hilbert space, and a concise exposition of related constructive fixed point theory that allows for a wide range of algorithms to construct solutions to problems in optimization, equilibrium theory, monotone inclusions, variational inequalities, and convex feasibility.
(via Semantic Scholar)
Source: ORCID
Added: November 16, 2021
2017 journal article
Analysis and prediction of protein folding energy changes upon mutation by element specific persistent homology
Bioinformatics, 7.
MeSH headings : Algorithms; Computational Biology / methods; Mutagenesis; Mutation / physiology; Protein Folding; Protein Stability; Proteins / chemistry; Proteins / genetics; Proteins / metabolism; Software; Structural Homology, Protein; Thermodynamics
TL;DR:
The present approach is found to outperform other existing methods in the predictions of globular protein stability changes upon mutation, and has a 84% higher Pearson correlation coefficient than the current state‐of‐the‐art empirical methods.
(via Semantic Scholar)
Source: ORCID
Added: August 22, 2021
2017 journal article
TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions
PLOS Computational Biology, 13(7), e1005690.
Ed(s): R. Dunbrack
MeSH headings : Computational Biology / methods; Image Processing, Computer-Assisted; Machine Learning; Membrane Proteins / chemistry; Membrane Proteins / metabolism; Membrane Proteins / physiology; Models, Statistical; Molecular Dynamics Simulation; Neural Networks, Computer; Protein Binding; Protein Folding
TL;DR:
A multi-task multichannel topological convolutional neural network (MM-TCNN) that outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein foldingfree energy changes, and mutation induced membrane protein folding free energy changes.
(via Semantic Scholar)
Source: ORCID
Added: August 22, 2021
2017 book
Numerical Solution of Differential Equations
In Cambridge University Press.
UN Sustainable Development Goal Categories
4. Quality Education
(OpenAlex)
Source: ORCID
Added: January 1, 2021
2017 conference paper
Real-Time Implementation of a LQR-Based Controller for the Stabilization of a Double Inverted Pendulum
In S.-long Ao, O. Castillo, C. Douglas, D. D. Feng, & A. Korunsky (Eds.), International MultiConference of Engineers and Computer Scientists : IMECS 2017: 15-17 March, 2017, the Royal Garden Hotel, Kowloon, Hong Kong: Vol. I (pp. 245–250). Hong Kong: Newswood Limited.
Ed(s): S. Ao, O. Castillo, C. Douglas, D. Feng & A. Korunsky
Event: International MultiConference of Engineers and Computer Scientists on March 15-17, 2017
Source: NC State University Libraries
Added: October 31, 2020
2017 article
Degree-optimal moving frames for rational curves
(2017, March 8).
Source: ORCID
Added: September 16, 2020
Citation Index includes data from a number of different sources. If you have questions about the sources of data in the Citation Index or need a set of data which is free to re-distribute, please contact us.
Certain data included herein are derived from the Web of Science© and InCites© (2024) of Clarivate Analytics. All rights reserved. You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.
