Extreme learning machines for feature learning by Liyanaarachchi Lekamalage, Chamara Kasun

“…Furthermore, the hidden layer parameters of ELM are randomly selected independent from input data, and only the output parameters are tuned. Input data might contain noise and unwanted information, which might affect machine learning algorithms generalization capability. …”
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Broad learning vs. deep learning by Gu, Haowei

“…In this project, the result of comparisons between Broad Learning model and Deep Learning model with Fashion MNIST and noisy MNIST dataset which illustrates the effect of Broad Learning model and whether it would be an alternative method for Deep Learning. …”
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Development of vision-based terrain recognition method for lower limb exoskeleton for outdoor environments by Gupta, Paluk

“…The heart of the system is a deep learning model, specifically Convolutional Neural Network (CNN). …”
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Analysis of online learning algorithms in machine learning by Wang, Z

“…Further, we develop a new continuous-time stochastic gradient descent method for optimizing over the stationary distribution of SDE models. …”

Deep Reinforcement Learning in complex environments by Nardelli, N

“…The presence of multiple agents breaks some of the key assumptions that provide necessary stability to standard learning methods, creating unique and interesting problems. …”

A unified framework of active transfer learning for cross-system recommendation by Zhao, Lili, Pan, Sinno Jialin, Yang, Qiang

“…In this paper, we propose a new transfer learning framework for recommender systems, which relaxes the above assumption to facilitate flexible knowledge transfer across different systems with low cost by using an active learning principle to construct entity correspondences across systems. …”
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Engineering nano-nodular pattern on the substrate surface by tuning phase inversion to construct ultrapermselective ion-separation nanofiltration membrane by Zhao, Yali, Li, Can, Liao, Yuan, Yin, Yurong, Wang, Rong, Chen, Dongliang

“…This work pioneers a new approach to tuning the PA layer structure, which can be readily achieved, and offers a fresh perspective on constructing high-performance NF membranes.…”
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Student teachers learning to use Assessment for Learning in schools by Tan Chia Chun, D

“…<p>Assessment for Learning (AfL) has been seen as a key aspect of teaching and learning for almost two decades, since the seminal review by Black and Wiliam (1998a). …”

Online learning by Kashish Minocha.

“…This is potentially due to a lack of interest in programming arising out of conventional methods of instruction. Since programming in C lays the foundation for a variety of advanced engineering study, efforts are necessary to kindle and sustain interests of the students while learning this module. …”
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Evolutionary computing for unsupervised clustering methods by Do, Anh Duc

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Universal machine learning classifier using extreme learning machines by Chen, Jinnan

“…We also applied the extreme learning machine with some modification as the core part into our algorithm and use several evaluation indexes to give an objective and comprehensive analysis of the proposed method.…”
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Tactile identification of textures using machine learning/ deep learning by Goh, Jun Bin

“…This project seeks to establish a method to identify an object, based on its haptic properties, and using Machine Learning and/or Deep Learning techniques. …”
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Diagrammatic Representation and Inference : 12th International Conference, Diagrams 2021, Virtual, September 28-30, 2021, Proceedings / by Diagrams (Conference) (12th : 2021 : Online) 643173, Basu, Amrita, 1953-, editor 643175, Stapleton, Gem, editor 643176, Linker, Sven, editor 643177, Legg, Catherine, editor 643178, Manalo, Emmanuel, editor 643179, Viana, Petrucio, editor 643180

Towards robust sensing and recognition : from statistical learning to transfer learning by Yang, Jianfei

“…To this end, we propose a Siamese deep model with both spatial and temporal feature extractors, which discards the intrinsic noises of CSI data during feature learning. The proposed method also allows user to fine-tune the system using few samples, and thus is user-friendly. …”
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Weighted online sequential extreme learning machine for class imbalance learning by Lin, Zhiping, Mirza, Bilal., Toh, Kar-Ann.

“…Most of the existing sequential learning methods for class imbalance learn data in chunks. …”
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Learning driver-specific behavior for overtaking : a combined learning framework by Lu, Chao, Wang, Huaji, Lv, Chen, Gong, Jianwei, Xi, Junqiang, Cao, Dongpu

“…However, traditional offline learning methods lack the ability to adapt to individual driving behavior. …”
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Effects of problem-based learning on EFL learning: a systematic review by Guo, Qian, Jamil, Halimah, Ismail, Lilliati, Luo, Shujie, Sun, Zhubin

“…Problem-based learning (PBL) is an innovative pedagogical approach that facilitates students’ self-regulated learning, thereby improving their English proficiency. …”
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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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Librarian class attendance : methods, outcomes and opportunities by Cmor, Dianne, Marshall, Victoria.

“…This paper describes the setting, methods, and outcomes associated with having librarians attend courses as active members in an evolving learning environment. …”
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Online learning with kernels by Fan, Haijin

“…Kernel methods are popular nonparametric modeling tools in machine learning. …”
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