Suchergebnisse - "algorithms in high dimensions"

Algorithms for Numerical Analysis in High Dimensions von Beylkin, Gregory, Mohlenkamp, Martin J.

“… Nearly every numerical analysis algorithm has computational complexity that scales exponentially in the underlying physical dimension. The separated …”
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Improved Nelder-Mead algorithm in high dimensions with adaptive parameters based on Chebyshev spacing points von Mehta, V.K.

“… The work presented here concerns such values of the Nelder-Mead algorithm's parameters that help improve the convergence and success rate of the algorithm in high dimensions …”
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An Auxiliary Variable Method for Markov Chain Monte Carlo Algorithms in High Dimension von Marnissi, Yosra, Chouzenoux, Emilie, Benazza-Benyahia, Amel, Pesquet, Jean-Christophe

“… In this paper, we are interested in Bayesian inverse problems where either the data fidelity term or the prior distribution is Gaussian or driven from a …”
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Population Monte Carlo Algorithm in High Dimensions von Lee, Jeong Eun, McVinish, Ross, Mengersen, Kerrie

“… The population Monte Carlo algorithm is an iterative importance sampling scheme for solving static problems. We examine the population Monte Carlo algorithm in …”
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Bi-quadratic polynomial approach for global convergent algorithm in high dimensions coefficient inverse problems von Wang, Quan-Fang

“… Sequential minimization algorithm in convexification approach established a stable approximate solution via minimizing a finite sequence of strictly convex …”
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Nested sampling for physical scientists von Ashton, Greg, Bernstein, Noam, Buchner, Johannes, Chen, Xi, Csányi, Gábor, Fowlie, Andrew, Feroz, Farhan, Griffiths, Matthew, Handley, Will, Habeck, Michael, Higson, Edward, Hobson, Michael, Lasenby, Anthony, Parkinson, David, Pártay, Livia B., Pitkin, Matthew, Schneider, Doris, Speagle, Joshua S., South, Leah, Veitch, John, Wacker, Philipp, Wales, David J., Yallup, David

“… The principles of nested sampling are summarized and recent developments using efficient nested sampling algorithms in high dimensions surveyed, including methods for sampling from the constrained prior …”
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Optimal Scaling for the Proximal Langevin Algorithm in High Dimensions von Pillai, Natesh S

“… The Metropolis-adjusted Langevin (MALA) algorithm is a sampling algorithm that incorporates the gradient of the logarithm of the target density in its proposal …”
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An opposition-based butterfly optimization algorithm with adaptive elite mutation in solving complex high-dimensional optimization problems von Li, Yu, Yu, Xiaomei, Liu, Jingsen

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Quantum Circuits for partial differential equations via Schrödingerisation von Hu, Junpeng, Jin, Shi, Liu, Nana, Zhang, Lei

“… Quantum computing has emerged as a promising avenue for achieving significant speedup, particularly in large-scale PDE simulations, compared to classical …”
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Optimal scaling and diffusion limits for the Langevin algorithm in high dimensions von Pillai, Natesh S, Stuart, Andrew M, Thiéry, Alexandre H

“… The Metropolis-adjusted Langevin (MALA) algorithm is a sampling algorithm which makes local moves by incorporating information about the gradient of the …”
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Diffusion limits of the random walk Metropolis algorithm in high dimensions von Mattingly, Jonathan C, Pillai, Natesh S, Stuart, Andrew M

“… Diffusion limits of MCMC methods in high dimensions provide a useful theoretical tool for studying computational complexity. In particular, they lead directly …”
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Principled Statistical Approaches for Sampling and Inference in High Dimensions von Dwivedi, Raaz

“… : We provide explicit non-asymptotic guarantees for state-of-the-art sampling algorithms in high dimensions that can help the user pick a sampling method …”
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Quantum Circuits for partial differential equations via Schrödingerisation von Hu, Junpeng, Shi, Jin, Liu, Nana, Zhang, Lei

“… Quantum computing has emerged as a promising avenue for achieving significant speedup, particularly in large-scale PDE simulations, compared to classical …”
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Geometry of multidimensional Farey summation algorithm and frieze patterns von Karpenkov, Oleg, Matty van Son

“… In this paper we develop a new geometric approach to subtractive continued fraction algorithms in high dimensions …”
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A Catalyst Framework for the Quantum Linear System Problem via the Proximal Point Algorithm von Kim, Junhyung Lyle, Nai-Hui Chia, Kyrillidis, Anastasios

“… Solving systems of linear equations is a fundamental problem, but it can be computationally intensive for classical algorithms in high dimensions …”
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Optimal Scaling of Random-Walk Metropolis Algorithms on General Target Distributions von Yang, Jun, Roberts, Gareth O, Rosenthal, Jeffrey S

“… One main limitation of the existing optimal scaling results for Metropolis--Hastings algorithms is that the assumptions on the target distribution are …”
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alpha-Shape Based Classification with Applications to Optical Character Recognition von Packer, E., Tzadok, A., Kluzner, V.

“… -shape algorithms in high dimensions. We further show how to inelegantly choose suitable α …”
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A self-stabilizing MSA algorithm in high-dimension data stream von Kong, Xiangyu, Hu, Changhua, Han, Chongzhao

“… Minor subspace analysis (MSA) is a statistical method for extracting the subspace spanned by all the eigenvectors associated with the minor eigenvalues of the …”
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High-dimensional scaling limits of piecewise deterministic sampling algorithms von Bierkens, Joris, Kamatani, Kengo, Roberts, Gareth O

“… ) the scaling limits show qualitatively very different and rich behaviour. Based on these scaling limits the performance of the two algorithms in high dimensions can be compared …”
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Sparse feature selection by information theory von Guangyao Zhou, Geman, Stuart, Buhmann, Joachim M.

“… Learning sparse structures in high dimensions defines a combinatorial selection problem of e.g. informative feature dimensions and a subsequent estimation task …”
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