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Journal of Machine Learning Research, ISSN 1532-4435, 04/2012, Volume 13, pp. 981 - 1006
The Nystrom method is an efficient technique to generate low-rank matrix approximations and is used in several large-scale learning applications. A key aspect... 
Nyström method | Large-scale learning | Ensemble methods | Low-rank approximation | large-scale learning | MATRIX | ensemble methods | nystrom method | ALGORITHMS | low-rank approximation | AUTOMATION & CONTROL SYSTEMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Mediterranean Journal of Mathematics, ISSN 1660-5446, 08/2016, Volume 13, Issue 4, pp. 2271 - 2285
In this work, we give the general framework for constructing trigonometrically fitted symplectic Runge-Kutta-Nystrom (RKN) methods from symplectic... 
65L05 | Runge-Kutta-Nystrom methods | MATHEMATICS | Hamiltonian systems | MATHEMATICS, APPLIED | FREQUENCY EVALUATION | Partitioned Runge-Kutta methods | ODES | NUMERICAL-INTEGRATION | symplectic methods | trigonometrical fitting | OSCILLATING SOLUTIONS | INITIAL-VALUE PROBLEMS | Computer science | International trade | Methods | Resveratrol
Journal Article
Neurocomputing, ISSN 0925-2312, 04/2017, Volume 234, pp. 116 - 125
Nyström method is a widely used matrix approximation method for scaling up kernel methods, and existing sampling strategies for Nyström method are proposed to... 
Nyström method | Matrix approximation | Kernel methods | Predictive sampling strategy | Nystrom method | MONTE-CARLO ALGORITHMS | MATRIX DECOMPOSITIONS | SVD | APPROXIMATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Computer science | Methods
Journal Article
Computers and Mathematics with Applications, ISSN 0898-1221, 2011, Volume 61, Issue 11, pp. 3381 - 3390
An explicit optimized Runge–Kutta–Nyström method with four stages and fifth algebraic order is developed. The produced method has variable coefficients with... 
Runge–Kutta–Nyström methods | Initial value problems | Phase-lag | Numerical solution | Explicit methods | Amplification factor | RungeKuttaNystrm methods | Runge-Kutta-Nystrom methods | MATHEMATICS, APPLIED
Journal Article
Computer Physics Communications, ISSN 0010-4655, 12/2014, Volume 185, Issue 12, pp. 3151 - 3155
Journal Article
Applied Mathematics and Information Sciences, ISSN 1935-0090, 2013, Volume 7, Issue 2, pp. 433 - 437
Journal Article
IEEE Transactions on Antennas and Propagation, ISSN 0018-926X, 07/2015, Volume 63, Issue 7, pp. 3111 - 3121
Journal Article
Journal of Machine Learning Research, ISSN 1533-7928, 12/2005, Volume 6, pp. 2153 - 2175
A problem for many kernel-based methods is that the amount of computation required to find the solution scales as O(n(3)), where n is the number of training... 
Nyström method | Kernel methods | Randomized algorithms | Gram matrix | Nystrom method | DIMENSIONALITY REDUCTION | randomized algorithms | kernel methods | EIGENMAPS | AUTOMATION & CONTROL SYSTEMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Journal of Computational and Applied Mathematics, ISSN 0377-0427, 10/2012, Volume 236, Issue 16, pp. 3880 - 3889
Journal Article
by Ma, LD and Shi, L and Wu, ZM
INVERSE PROBLEMS, ISSN 0266-5611, 07/2019, Volume 35, Issue 7, p. 75002
Kernel methods are attractive in data analysis as they can model nonlinear similarities between observations and provide means to rich representations, both of... 
RATES | MATHEMATICS, APPLIED | mini-max optimal rates | Nystrom subsampling method | indefinite kernels | PHYSICS, MATHEMATICAL | coefficient-based regularized regression | KERNELS
Journal Article
Journal of Machine Learning Research, ISSN 1532-4435, 04/2016, Volume 17, pp. 1 - 65
Journal Article