Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal Outcomes by Bosschieter, Tomas M., Xu, Zifei, Lan, Hui, Lengerich, Benjamin J., Nori, Harsha, Painter, Ian, Souter, Vivienne, Caruana, Rich

“…We use an Explainable Boosting Machine (EBM), a high-accuracy glass-box learning method, for the prediction and identification of important risk factors. …”
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Image classification by multimodal subspace learning by Yu, Jun, Lin, Feng, Seah, Hock Soon, Li, Cuihua, Lin, Ziyu

“…According to the “Patch Alignment” Framework, we developed a new subspace learning method, termed Semi-Supervised Multimodal Subspace Learning (SS-MMSL), in which we can encode different features from different modalities to build a meaningful subspace. …”
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Transfer-recursive-ensemble learning for multi-day COVID-19 prediction in India using recurrent neural networks by Chakraborty, Debasrita, Goswami, Debayan, Ghosh, Susmita, Ghosh, Ashish, Chan, Jonathan H., Wang, Lipo

“…Each of the four models then gives 7-day ahead predictions using the recursive learning method for the Indian test data. The final prediction comes from an ensemble of the predictions of the different models. …”
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User Profiling Based on Nonlinguistic Audio Data by Shen, Jiaxing, Cao, Jiannong, Lederman, Oren, Tang, Shaojie, Pentland, Alex

“…Secondly, we propose a gender-assisted multi-task learning method to combat dynamics in human behavior by integrating gender differences and the correlation of personality traits. …”
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E-learning for mobile learning platform by MacInnes, Catriona

“…By studying the way people learn, methods can be created to increase learning potential and efficiency. …”
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Data-efficient modeling for power consumption estimation of quadrotor operations using ensemble learning by Dai, Wei, Zhang, Mingcheng, Low, Kin Huat

“…We employed an ensemble learning method, namely stacking, to develop a data-driven model using flight records of three different types of quadrotors. …”
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Aiding therapy using speech emotion recognition by Koh, En Rong

“…We will explore the use of a Convolutional Neural network, a type of Deep Learning method, to train and predict human emotions. …”
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Video surveillance for intelligent transportation system by Liu, Jiamin

“…Artificial Intelligence (AI) with matching learning method had been widely used in this field in recent years. …”
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Adaptive function modal learning neural networks by Kang, Miao

“…Modal learning method is a neural network learning term that refers to a single neural network which combines with more than one mode of learning. …”
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Medicine distribution pattern detection in pharmaceutical supply chains: a new Kth-proximity density-distance-based method by Delgoshaei, Aidin, Mohd Ariffin, Mohd Khairol Anuar

“…Originality/value: In this research, the machine learning method based on the nearest neighbor has been used for the first time in the design of the supply chain network.…”
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Statistical modeling of fully nonlinear hydrodynamic loads on offshore wind turbine monopile foundations using wave episodes and targeted CFD simulations through active sampling by Guth, Stephen, Katsidoniotaki, Eirini, Sapsis, Themistoklis P.

“…The novelty of our framework lies in its efficient construction of the surrogate model, utilizing the Gaussian process regression machine learning technique and a Bayesian active learning method to sequentially sample wave episodes that contribute to accurate predictions of extreme hydrodynamic forces. …”
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Lane detection algorithm for autonomous vehicle using machine learning by Wu, Guan Jie

“…Hence, there is a need to shift from traditional computer vision algorithms to deep learning method in feature extraction. Convolution neural network (CNN) has been the de facto feature extraction module in computer vision. …”
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The Effect Of Blended Learning And critical Thinking On Tertiary EFL Argumentative Writing In China by Wang, Yuling

“…With the rapid development of Information and Communications Technology (ICT), the blended learning method is widespread in English-as-a-Foreign-Language (EFL) instruction. …”
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Computer Supported Cooperative Work and Social Computing : 15th CCF Conference, ChineseCSCW 2020, Shenzhen, China, November 7-9, 2020, Revised Selected Papers / by CCF Conference on Computer Supported Cooperative Work and Social Computing (15th : 2020 : Shenzhen, China), organiser 642953, Sun, Yuqing, editor 642954, Liu, Dongning, editor 642955, Liao, Hao, 1986-, editor 642956, Fan, Hongfei, editor 642957, Gao, Liping, editor 642958

Refining learning models in grammatical inference by Wang, Xiangrui

“…We introduce the use of recurrent neural networks (RNNs) and present a pruning learning method to avoid the exponential space costs. …”
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Robot programming using augmented reality by Chong, Jonathan Wun Shiung

“…The Piecewise Linear Parameterization (PLP) algorithm and a curve learning method based on Bayesian neural networks and reparameterization are proposed. …”
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A Non‐Intrusive Machine Learning Framework for Debiasing Long‐Time Coarse Resolution Climate Simulations and Quantifying Rare Events Statistics by Barthel Sorensen, B., Charalampopoulos, A., Zhang, S., Harrop, B. E., Leung, L. R., Sapsis, T. P.

“…Here, the scope is to formulate a learning method that allows for correction of dynamics and quantification of extreme events with longer return period than the training data. …”
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15.665B Power and Negotiation, Fall 2002 by Williams, Michele

“…You will learn and practice the technical skills and analytic frameworks that are necessary to negotiate successfully with peers from other top business schools, and you will learn methods for developing the powerful social capital you will need to rise in the executive ranks of any organization. …”
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Exploring disease axes as an alternative to distinct clusters for characterizing sepsis heterogeneity by Zhang, Zhongheng, Chen, Lin, Liu, Xiaoli, Yang, Jie, Huang, Jiajie, Yang, Qiling, Hu, Qichao, Jin, Ketao, Celi, Leo A., Hong, Yucai

“…The top-down transfer learning method (model trained on cohorts with greater severity was transferred to cohorts with lower severity score) had a higher NMI value than the bottom-up approach (median [Q1, Q3]: 0.64 [0.49, 0.78] vs. 0.23 [0.2, 0.31], p < 0.001). …”
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Hermes: Boosting the Performance of Machine-Learning-Based Intrusion Detection System through Geometric Feature Learning by Zhang, Chaoyu, Shi, Shanghao, Wang, Ning, Xu, Xiangxiang, Li, Shaoyu, Zheng, Lizhong, Marchany, Randy, Gardner, Mark, Hou, Y. Thomas, Lou, Wenjing

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