Results 1 to 10 of about 859,071 (262)
A Rapid Convergent Low Complexity Interference Alignment Algorithm for Wireless Sensor Networks
Interference alignment (IA) is a novel technique that can effectively eliminate the interference and approach the sum capacity of wireless sensor networks (WSNs) when the signal-to-noise ratio (SNR) is high, by casting the desired signal and interference
Lihui Jiang +4 more
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A novel three-term conjugate gradient approach for deep neural network training [PDF]
This paper presents a new three-term conjugate gradient (CG) method for large-scale unconstrained optimization, with application to training deep neural networks.
Faeze Sadat Hosseini-Mighan, Ali Ashrafi
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An S-Hybridization Technique Using Two-Directional Optimization
In this paper, we study a recently established s-hybrid approach for generating gradient descent methods for solving optimization tasks. We present an s-hybrid variant of the accelerated double-direction method.
Vladimir Rakočević +1 more
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Probabilistic Line Searches for Stochastic Optimization
12 pages, including ...
Mahsereci, M., Hennig, P.
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An upgrade to the quasi-Newton (QN) family of methods for solving unconstrained optimization problems is proposed. This research focuses on a detailed investigation of the Barzilai and Borwein (BB) gradient methods.
Predrag S. Stanimirović +3 more
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Euphemisms and dysphemism: in search of a boundary line
Straightforward remarks may sometimes be regarded as either an offence or an indelicacy. That is the reason why, to avoid the danger of being perceived vulgar or illmannered, language users prefer to employ a range of so-called concealing mechanisms ...
Bożena Duda
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Joint trade-off optimization algorithm based on cooperative spectrum sensing throughput
The achievable data throughput of the cognitive network was modeled to optimize the overhead and performance of the cooperative system thoroughly.Considering the soft data combination decision,the joint trade-off optimization of the local sampling number
Guo-qing JI, Gang WANG, Hong-bo ZHU
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An Efficient Penalty Method without a Line Search for Nonlinear Optimization
In this work, we integrate some new approximate functions using the logarithmic penalty method to solve nonlinear optimization problems. Firstly, we determine the direction by Newton’s method.
Assma Leulmi
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Adaptive Backtracking Line Search
Backtracking line search is foundational in numerical optimization. The basic idea is to adjust the step-size of an algorithm by a constant factor until some chosen criterion (e.g. Armijo, Descent Lemma) is satisfied. We propose a novel way to adjust step-sizes, replacing the constant factor used in regular backtracking with one that takes into account
Joao V. Cavalcanti +2 more
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Automated 3D Tumor Segmentation From Breast DCE-MRI Using Energy-Tuned Minimax Optimization
Breast cancer (BC) is a multifaceted genetic malignancy that accounts for the majority of cancer fatalities in women. Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) is predominant in evaluating perfusion, extravascular-extracellular ...
Priyadharshini Babu +2 more
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