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   Articles with "limited memory" as a keyword



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Proximal Limited-Memory Quasi-Newton Methods for Scenario-based Stochastic Optimal Control

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recommendations! Published in 2017 at "IFAC-PapersOnLine"

DOI: 10.1016/j.ifacol.2017.08.1372

Abstract: Abstract Stochastic optimal control problems are typically of rather large scale involving millions of decision variables, but possess a certain structure which can be exploited by first-order methods such as forward-backward splitting and the alternating… read more here.

Keywords: limited memory; proximal limited; stochastic optimal; optimal control ... See more keywords

A new efficient training strategy for deep neural networks by hybridization of artificial bee colony and limited-memory BFGS optimization algorithms

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recommendations! Published in 2017 at "Neurocomputing"

DOI: 10.1016/j.neucom.2017.05.061

Abstract: Abstract Working up with deep learning techniques requires profound understanding of the mechanisms underlying the optimization of the internal parameters of complex structures. The major factor limiting this understanding is that there exist only a… read more here.

Keywords: limited memory; training strategy; optimization; bfgs ... See more keywords
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Limited memory optimizes cooperation in social dilemma experiments

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recommendations! Published in 2021 at "Royal Society Open Science"

DOI: 10.1098/rsos.210653

Abstract: Cooperation is one of the key collective behaviours of human society. Despite discoveries of several social mechanisms underpinning cooperation, relatively little is known about how our neural functions affect cooperative behaviours. Here, we study the… read more here.

Keywords: memory capacity; limited memory; dilemma experiments; memory ... See more keywords
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A Limited Memory BFGS Based Unimodular Sequence Design Algorithm for Spectrum-Aware Sensing Systems

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3192848

Abstract: Unimodular sequences with good correlation and spectral properties are desirable in numerous applications such as active remote sensing and communication systems. Therefore, designing sequences with stopband and correlation sidelobe constraints has gained a lot of… read more here.

Keywords: problem; memory bfgs; design; limited memory ... See more keywords
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Limited-Memory Receive Filter Design for Massive MIMO Radar in Signal-Dependent Interference

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recommendations! Published in 2022 at "IEEE Signal Processing Letters"

DOI: 10.1109/lsp.2022.3188176

Abstract: This letter proposes a limited-memory receive filter design to maximize the output signal-to-interference-plus-noise ratio (SINR) of massive multiple-input multiple-output (MIMO) radar. The associated problem is a minimum variance distortionless response (MVDR) one which can be… read more here.

Keywords: memory receive; interference; limited memory; receive filter ... See more keywords
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Two-dimensional anisotropic magnetotelluric inversion using a limited-memory quasi-Newton method

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recommendations! Published in 2021 at "GEOPHYSICS"

DOI: 10.1190/geo2020-0488.1

Abstract: We have developed a two-dimensional (2D) anisotropic magnetotelluric (MT) inversion algorithm that uses a limited-memory quasi-Newton (QN) method for bounds-constrained optimization. This algorithm solves the inverse problem, which is non-linear, by iterative minimization of linearized… read more here.

Keywords: anisotropic; limited memory; anisotropic magnetotelluric; two dimensional ... See more keywords
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Learning dynamics with social comparisons and limited memory

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recommendations! Published in 2019 at "Theoretical Economics"

DOI: 10.17863/cam.35979

Abstract: We study models of learning in games where agents with limited memory use social information to decide when and how to change their play. When agents only observe the aggregate distribution of payoffs and only… read more here.

Keywords: limited memory; aggregate play; memory; close nash ... See more keywords

An Active Set Limited Memory BFGS Algorithm for Machine Learning

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recommendations! Published in 2022 at "Symmetry"

DOI: 10.3390/sym14020378

Abstract: In this paper, a stochastic quasi-Newton algorithm for nonconvex stochastic optimization is presented. It is derived from a classical modified BFGS formula. The update formula can be extended to the framework of limited memory scheme.… read more here.

Keywords: active set; limited memory; algorithm; machine learning ... See more keywords