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Published in 2021 at "Journal of Computational Chemistry"
DOI: 10.1002/jcc.26522
Abstract: Numerical optimization is a common technique in various areas of computational chemistry, molecular modeling and drug design. It is a key element of 3D techniques, for example, the optimization of protein–ligand poses and small‐molecule conformers.…
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Keywords:
lsl bfgs;
step;
bfgs algorithm;
chemistry ... See more keywords
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Published in 2017 at "Scientific Reports"
DOI: 10.1038/s41598-017-09294-y
Abstract: In seismic waveform tomography, or full-waveform inversion (FWI), one effective strategy used to reduce the computational cost is shot-encoding, which encodes all shots randomly and sums them into one super shot to significantly reduce the…
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Keywords:
shot encoding;
shot;
waveform;
bfgs algorithm ... See more keywords
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Published in 2019 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2019.2891088
Abstract: The limited memory version of the Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) algorithm is the most popular quasi-Newton algorithm in machine learning and optimization. Recently, it was shown that the stochastic L-BFGS (sL-BFGS) algorithm with the variance-reduced stochastic gradient…
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Keywords:
stochastic bfgs;
accelerated linearly;
bfgs;
bfgs algorithm ... See more keywords
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Published in 2017 at "Journal of Inequalities and Applications"
DOI: 10.1186/s13660-017-1453-5
Abstract: In this paper, a modified BFGS algorithm is proposed for unconstrained optimization. The proposed algorithm has the following properties: (i) a nonmonotone line search technique is used to obtain the step size αk$\alpha_{k}$ to improve…
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Keywords:
nonmonotone bfgs;
bfgs algorithm;
unconstrained optimization;
modified nonmonotone ... See more keywords