Pruning methods for RBF networks by Tarannum Shakir.

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Signature methods in machine learning by Lyons, T, McLeod, A

Signature methods in machine learning by Lyons, T, McLeod, AD

Feature selection for classification applications in neural network pruning by Gong, Rui

“…Then the neural network pruning problem is formulated as a feature selection problems, and feature selection methods are introduced to prune neural networks. …”
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Machine learning and deep learning methods for exchange-traded fund trading by Jeremia, Alexander

“…Machine Learning and Deep Learning has been growing in the popularity in many fields in the past few years especially in the field of Exchange Traded Funds (ETF) due to its ability to analyse large amount of data and detect patterns that might not be oblivious to traders. …”
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A comparative analysis of vitrification and two slow freezing methods for gonocyte-containing neonatal calf testicular tissue and subsequent in vitro culture by Tang, S, Jones, C, Davies, J, Lane, S, Coward, K

“…No significant differences were observed in the proportion of seminiferous tubules containing PGP9.5-positive germ cells when compared between the three methods. Comparable densities of germ cells per unit area were observed in the controlled/uncontrolled slow freezing groups, and the vitrification group (7.89 ± 1.83, 7.75 ± 1.75, and 7.92 ± 1.23/104 µm2 , respectively). …”

Methods and systems for ontology learning, exploitation, and analysis by Xing, Jiang

“…By using a full text parsing technique and incorporating both statistical and lexico-syntactic methods, the ontologies learned by our system are more concise and contain a richer semantics in terms of the range and number of semantic relations compared with alternative systems.…”
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Machine learning methods for Android malware detection by Xu, Zhengzi

“…To detect the malware before the installed time, and overcome the drawbacks of dynamic analysis and signature based analysis, the machine learning based malware detection methods has been proposed. …”
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SSCM2423 Numerical Methods 1 : Learning Module / by Shazirawati Mohd Puzi, author 618942

Analysis of TEM data using machine learning methods by Muhammed Imran Khairul Alam

“…This paper also presents a comparison of imaging techniques, such as filtering and machine learning methods, that would improve the quality of the raw liquid phase images.…”
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Ensemble hybrid learning methods for automated depression detection by Ansari, Luna, Ji, Shaoxiong, Chen, Qian, Cambria, Erik

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Predict marine vessels’ trajectory with machine learning methods by Cho, Siqi

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Exchange rate prediction based on machine learning methods by Hong, Yuyue

“…In this paper, we use machine learning methods mentioned above to forecast the exchange rate between five different currencies and the United States dollar. …”
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Stock market price forecasting with machine learning methods by Zhu, Huilin

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Sparse machine learning methods for financial signal processing by Pucha Srinivasa Sai Chakravarthy

“…The prime motivation of this thesis is to find applications of decision sciences and machine learning techniques to solve the mean – variance optimization problem to construct portfolios that are optimal and simple with the aid of less computation intensive methods. …”
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Morphological learning in spiking neurons: a new hardware efficient maching learning method by Jahagirdar, Kavya

“…The latest developments in the research of spiking neural network models have shown that unlike the classic neural network models, these models communicate via precisely timed neuron spikes, thus making them a closer representation of the biological neurons. ‘Morphological Learning in Spiking Neurons: A New Hardware Efficient Machine Learning Method’ explores the greater performance of spiking neurons with lumped non-linearity than their counterparts with linear synaptic summation of signals. …”
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How to learn Chinese characters? Exploring the effectiveness of different learning methods in young Singaporean children by Toh, Wendy Hwee Bin

“…The character learning experiments used the same sets of Chinese characters to study three different modalities (viewing, free writing and structured writing) and several different encoding methods (Pinyin – romanised phonetic coding system of the Chinese script, whole character, stroke sequence and radical knowledge) in six learning conditions. …”
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Two-step machine learning enables optimized nanoparticle synthesis by Mekki-Berrada, Flore, Ren, Zekun, Huang, Tan, Wong, Wai Kuan, Zheng, Fang, Xie, Jiaxun, Tian, Isaac Parker Siyu, Jayavelu, Senthilnath, Mahfoud, Zackaria, Bash, Daniil, Hippalgaonkar, Kedar, Khan, Saif, Buonassisi, Tonio, Li, Qianxiao, Wang, Xiaonan

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Fuzzy granular computing classifier with practicle swarm optimization learning method / by Saber Salehi, 1982-, author 599901, Ali Selamat, supervisor 389865, Fakulti Kejuruteraan. Sekolah Komputeran 619086

Fuzzy granular computing classifier with practicle swarm optimization learning method / by Saber Salehi, 1982-, author 599901