Speeding up deep neural network training with decoupled and analytic learning by Zhuang, Huiping

“…A fully decoupled learning method using delayed gradients (FDG) is first proposed which addresses all the three lockings. …”
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Transferring a deep learning model from healthy subjects to stroke patients in a motor imagery brain-computer interface by Nagarajan, Aarthy, Robinson, Neethu, Ang, Kai Keng, Chua, Karen Sui Geok, Chew, Effie, Guan, Cuntai

“…Motor imagery (MI) brain-computer interfaces (BCIs) based on electroencephalogram (EEG) have been developed primarily for stroke rehabilitation, however, due to limited stroke data, current deep learning methods for cross-subject classification rely on healthy data. …”
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High cycle fatigue characterisation and modelling of 316L stainless steel processed by laser powder bed fusion by Zhang, Meng

“…Lastly, considering the numerous influencing factors arising from the process and the associated failure behaviours, a neuro-fuzzy-based machine learning method was applied to provide an effective unifying approach for high cycle fatigue life prediction. …”
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Offline eLearning for undergraduates in health professions : a systematic review of the impact on knowledge, skills, attitudes and satisfaction by Wark, Petra A., Rasmussen, Kristine, Belisario, José Marcano, Molina, Joseph Antonio, Loong, Stewart Lee, Cotic, Ziva, Papachristou, Nikos, Riboli–Sasco, Eva, Car, Lorainne Tudor, Musulanov, Eve Marie, Zhang, Yanfeng, Kunz, Holger, George, Pradeep Paul, Heng, Bee Hoon, Wheeler, Erica Lynette, Al Shorbaji, Najeeb, Svab, Igor, Atun, Rifat, Majeed, Azeem, Car, Josip

“…To inform investments in offline eLearning, we need to establish its effectiveness in terms of gaining knowledge and skills, students’ satisfaction and attitudes towards eLearning. Methods: We conducted a systematic review of offline eLearning for students enrolled in undergraduate, health–related university degrees. …”
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Topics in Bayesian machine learning for finance by Spears, T

“…Further, we estimate an approximation to epistemic uncertainty via a pseudo-Bayesian deep learning method. This work demonstrates the utility of the model output for deciding the relative allocation of risk capital across trades. …”

Learning-enabled decision-making for autonomous driving: framework and methodology by Huang, Zhiyu

“…The personalized cost learning method outperforms general cost modeling methods, leading to a more human-like driving experience. …”
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Conflict-free urban air mobility planning with an airspace-resource-centric approach by Dai, Wei

“…Motivated by the absence of a precise power consumption model that can be applied to multiple eVTOL aircraft types, we use the ensemble learning method to model the power consumption of eVTOL aircraft. …”
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Fabrication and characterization of Algan/Gan high electron mobility transistors on silicon by Tham, Wai Hoe

“…Therefore, the current experimental studies suggest that the Ge doping approach is more suitable as a VTH tuning method. Although the fabrication cost of GaN-based devices can be reduced significantly through the incorporation with Si technology, there are several challenges which impede the incorporation of GaN-based devices with Si technology. …”
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Geometry guided supervised representation learning for classification by Li, Yue

“…However, the AE-based representation learning method, FAE-LG, is trained iteratively by using back-propagation (BP) that requires a significant amount of training time. …”
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Structured sparse representations for supervised and unsupervised learning by Zeng, Yijie

“…It is demonstrated that the proposed graph learning method, termed Adaptive Locality-constrained Clustering (ALC), generates more structured graph compared with predefined ones and provides better clustering performance on benchmark datasets. …”
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Development and optimization of polystyrene nanoparticle templated optical fiber platform for in vivo surface enhanced Raman spectroscopy. by Low, Vway Hau.

“…Two novel methods have been proposed to deposit the PS nanospheres monolayer on the fiber tip, including a simple ‘dip and dry’ method and PS nanospheres anchoring using chemical method. …”
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Fabrication of crosslinked spray dried alginate microparticles for encapsulation of bioactives by Lim, Yu Lin

“…In this study, crosslinked calcium alginate microparticles were successfully fabricated using a novel one-step spray drying method. The one step fabrication eliminates the need for multiple crosslinking and drying steps, as in traditional calcium alginate microparticles production. …”
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Graph representation learning by Zhang, Xinyi

“…Besides different techniques used in graph representation learning, according to the fineness of the objects for embedding, the graph representation learning methods can be mainly divided into node-level, edge-level, and graph-level representation learning methods. …”
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Deep reinforcement learning for optimal resource allocation by Ng, Steffi Si Yu

“…In addition, this project will practice parameter tuning methods on the algorithm to obtain a parameter set that can achieve the most optimal result.…”
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Fabrication and characterization of protein-based tissue scaffold by Ko, Kok Wei.

“…The SF scaffolds were prepared and fabricated via freeze drying method for five different sets of SF concentration - (5, 7.5, 10, 12.5, 15%) wt/wt. …”
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Descriptor learning using convex optimisation by Simonyan, K, Vedaldi, A, Zisserman, A

“…Both of these problems use large margin discriminative learning methods. The third contribution is a new method of obtaining the positive and negative training data in a weakly supervised manner. …”

Placing objects in context via inpainting for out-of-distribution segmentation by De Jorge, P, Volpi, R, Dokania, PK, Torr, PHS, Rogez, G

“…In our experiments, we present different anomaly segmentation datasets based on POC-generated data and show that POC can improve the performance of recent state-of-the-art anomaly fine-tuning methods across several standardized benchmarks. …”

Deep learning with constrained data resource by Mao, Jiangtian

“…The method can achieve a better accuracy compared to simple full-supervised learning methods, especially the problem becomes to a one-shotting problem.…”
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Ultralight and Highly Elastic Graphene/Lignin-Derived Carbon Nanocomposite Aerogels with Ultrahigh Electromagnetic Interference Shielding Performance by Zhang, Youfang, Wang, Peiyu, Pei, Yongmao, Chen, Mingji, Lu, Xuehong, Zeng, Zhihui, Wang, Changxian, Seyed Shahabadi, Seyed Ismail

“…Ultralight and highly elastic reduced graphene oxide (RGO)/lignin-derived carbon (LDC) composite aerogels with aligned micron-sized pores and cell walls are prepared using a facile freeze-drying method. The presence of a small fraction of LDC in the cell walls enhances the interfacial polarization effect while almost maintaining the amount of charge carriers and conductivity of the cell walls, greatly boosting the wave absorption capability of the cell walls. …”
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Machine learning for mathematical question difficulty classification by Pang, Jarald Qi Kai

“…The same 4 machine learning methods were then again used to classify the difficulty of each question using the vectorized question and predicted topic. …”
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