Deep reinforcement learning for optimal resource allocation by Ng, Steffi Si Yu

“…Hence, there is a need to use methods that do not increase production cost to improve productivity such as optimizing scheduling of activities and resources in a production. …”
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Query cost estimation in DBMS with deep learning by Acharya, Atul

“…With the recent rise of ML for DB, the database community explored the use of learned methods in cost and cardinality estimation. …”
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Natural robustness of machine learning in the open world by Wei, Hongxin

“…Secondly, classic machine learning methods are built on the i.i.d. assumption that training and testing data are independent and identically distributed. …”
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Machine learning enabled multivariate analysis of neuroimages by Chen, Dawen

“…This project also aimed to implement and conduct various multi-variant and machine learning methodologies on fMRI scans in order to investigate analysis methods of neuroimages. …”
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Personalized question recommendation for English grammar learning by Fang, Lanting, Tuan, Luu Anh, Hui, Siu Cheung, Wu, Lenan

“…Additionally, we incorporated the proposed recommendation method into a Web‐based English grammar learning system and presented its performance evaluation in this paper. …”
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Active learning with applications in biomedical document annotation by Han, Xu

“…We also apply our active learning method for the task of named entity recognition. …”
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Residual learning diagnosis detection: an advanced residual learning diagnosis detection system for COVID-19 in industrial internet of things by Zhang, Mingdong, Chu, Ronghe, Dong, Chaoyu, Wei, Jianguo, Lu, Wenhuan, Xiong, Naixue

“…Early diagnosis and isolation are effective and imperative strategies for epidemic prevention and control. Most diagnostic methods for the COVID-19 is based on nucleic acid testing (NAT), which is expensive and time-consuming. …”
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Enhanced extreme learning machines for image classification by Cui, Dongshun

“…Among numerous machine learning methods, we choose the Extreme Learning Machine (ELM) for our image classification applications. …”
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Enabling open-ended questions in team-based learning using automated marking: impact on student achievement, learning and engagement by Tan, Sophia Huey Shan, Thibault, Guillaume, Chew, Anna Chia Yin, Rajalingam, Preman

“…Methods: MCQs and OEQs test scores of N = 66 students were automatically captured in Learning Activity Management System (LAMS) and were compared using a switching replications quasi-experimental design with pre- and post-tests to answer the research questions. …”
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Learning hierarchical review graph representations for recommendation by Liu, Yong, Yang, Susen, Zhang, Yinan, Miao, Chunyan, Nie, Zaiqing, Zhang, Juyong

“…Previous review-based recommendation methods usually employ sophisticated compositional models, such as Recurrent Neural Networks (RNN) and Convolutional Neural Networks (CNN), to learn semantic representations from the review data for recommendation. …”
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Development of a learning system for robot control by Leong, Marcus Khee Ing

“…This project aims to develop a learning algorithm that can learn the Jacobian matrix of the robot with the use of neural network and control the end-effector to follow a predefined trajectory without modelling the robot kinematics. …”
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Synthesizing photorealistic images with deep generative learning by Zheng, Chuanxia

“…Extensive experiments demonstrate superior performance compared to previous CNN-based methods on several datasets. Part 3 combines recognitive learning and the latest generative modeling into a holistic scene decomposition and completion framework, where a network is trained to decompose a scene into individual objects, infer their underlying occlusion relationships, and moreover imagine what the originally occluded objects may look like, while using only a single image as input. …”
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Elementwise overparameterisation for single and multi-task learning by Ribli, Vincent

“…To solve such an issue, methods such as overparameterisation, along with multi-task learning, have been proposed. …”
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Support app UI development with deep learning by Chow, Bernard Wei Jun

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Efficient HIK SVM learning for image classification by Wu, Jianxin

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Quantum photonic sensors array with machine learning by Ho, Ping-Chien

“…DQS-CV protocol can also be used to help improve machine learning which is called the supervised learning assisted by and entangled sensor network(SLAEN).SLAEN converge in less step compared to the conventional algorithm and can find better hyperplanes. …”
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Deep learning for anomaly detection in computational imaging by Du, Xinglin

“…For supervised method, three methods are used: multilayer perceptron, convolutional neural network and transfer learning. …”
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Unsupervised Learning for Generative Scene Editing and Motion by Fang, David S.

“…Unsupervised learning for images and videos is important for many applications in computer vision. …”
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Object recognition using deep learning features by Zhu, Daiqing

“…However, previous algorithms need to train classifier to rank proposal and learn from object class recognition datasets. That is time consuming since those classifiers need to be trained again when new object category comes and database grow. …”
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Differentiable Vector Graphics Rasterization for Editing and Learning by Li, Tzu-Mao, Lukac, Mike, Gharbi, Michael, Ragan-Kelley, Jonathan

“…We introduce a differentiable rasterizer that bridges the vector graphics and raster image domains, enabling powerful raster-based loss functions, optimization procedures, and machine learning techniques to edit and generate vector content. …”
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