Suchergebnisse - "ACTIVE learning"

Generative Adversarial Active Learning for Unsupervised Outlier Detection von Liu, Yezheng, Li, Zhe, Zhou, Chong, Jiang, Yuanchun, Sun, Jianshan, Wang, Meng, He, Xiangnan

“… Outlier detection is an important topic in machine learning and has been used in a wide range of applications. In this paper, we approach outlier detection as …”
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Active learning for data streams: a survey von Cacciarelli, Davide, Kulahci, Murat

“… Online active learning is a paradigm in machine learning that aims to select the most informative data points to label from a data stream. The problem of …”
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Active Learning Query Strategies for Classification, Regression, and Clustering: A Survey von Kumar, Punit, Gupta, Atul

“… Generally, data is available abundantly in unlabeled form, and its annotation requires some cost. The labeling, as well as learning cost, can be minimized by …”
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Hyperspectral Image Classification With Convolutional Neural Network and Active Learning von Cao, Xiangyong, Yao, Jing, Xu, Zongben, Meng, Deyu

“… Deep neural network has been extensively applied to hyperspectral image (HSI) classification recently. However, its success is greatly attributed to numerous …”
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Empirical investigation of active learning strategies von Pereira-Santos, Davi, Prudêncio, Ricardo Bastos Cavalcante, de Carvalho, André C.P.L.F.

“… Many predictive tasks require labeled data to induce classification models. The data labeling process may have a high cost. Several strategies have been …”
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Cost-Effective Active Learning for Deep Image Classification von Wang, Keze, Zhang, Dongyu, Li, Ya, Zhang, Ruimao, Lin, Liang

“… Recent successes in learning-based image classification, however, heavily rely on the large number of annotated training samples, which may require …”
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Barriers to student active learning in higher education von Børte, Kristin, Nesje, Katrine, Lillejord, Sølvi

“… This article reviews research that consistently, across borders and over time, reveals inertia in Higher Education institutions related to innovation in …”
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Combining X-Vectors and Bayesian Batch Active Learning: Two-Stage Active Learning Pipeline for Speech Recognition von Kundacina, Ognjen, Vincan, Vladimir, Miskovic, Dragisa

“… This paper introduces a novel two-stage active learning (AL) pipeline for automatic speech recognition (ASR), combining unsupervised and supervised AL methods …”
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Active Learning With Convolutional Neural Networks for Hyperspectral Image Classification Using a New Bayesian Approach von Haut, Juan Mario, Paoletti, Mercedes E., Plaza, Javier, Li, Jun, Plaza, Antonio

“… Hyperspectral imaging is a widely used technique in remote sensing in which an imaging spectrometer collects hundreds of images (at different wavelength …”
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Pool-Based Sequential Active Learning for Regression von Wu, Dongrui

“… Active learning (AL) is a machine-learning approach for reducing the data labeling effort. Given a pool of unlabeled samples, it tries to select the most …”
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Abstract 1468 PULSE: Empowering Department and Transforming Education von Wolyniak, Michael, Awong-Taylor, Judy, Brancaccio-Taras, Loretta, Finelli, Christopher, Lee, Mark, Lindsay, Sara, Ward, Jennifer Rhode

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Abstract 1706 Leveraging Desmos in the Biochemistry Curriculum to Improve Visual Literacy von Potratz, Jeffrey, Bichler, Katherine

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Meet, Greet, and Learn: A Content-Centric “Getting to Know You” Activity von Gray, Jennifer B.

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Machine learning assisted design of high entropy alloys with desired property von Wen, Cheng, Zhang, Yan, Wang, Changxin, Xue, Dezhen, Bai, Yang, Antonov, Stoichko, Dai, Lanhong, Lookman, Turab, Su, Yanjing

“… We formulate a materials design strategy combining a machine learning (ML) surrogate model with experimental design algorithms to search for high entropy …”
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A system active learning Kriging method for system reliability-based design optimization with a multiple response model von Xiao, Mi, Zhang, Jinhao, Gao, Liang

“… •A new method is proposed for system reliability-based design optimization.•The responses of all constraints from a multiple response model are …”
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Fault Diagnosis of Rotating Machinery With Limited Expert Interaction: A Multicriteria Active Learning Approach Based on Broad Learning System von Liu, Zeyi, Zhang, Jingfei, He, Xiao, Zhang, Qinghua, Sun, Guoxi, Zhou, Donghua

“… Recently, research on the fault diagnosis of rotating machinery, especially for the compound or unknown cases, has drawn increasing attention. Some advanced …”
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A comprehensive active learning method for multiclass imbalanced data streams with concept drift von Liu, Weike, Zhang, Hang, Ding, Zhaoyun, Liu, Qingbao, Zhu, Cheng

“… A challenge to many real-world applications is multiclass imbalance with concept drift. In this paper, we propose a comprehensive active learning method for …”
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Surrogate-assisted reliability-based design optimization: a survey and a unified modular framework von Moustapha, Maliki, Sudret, Bruno

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Practical Active Learning Stations to Transform Existing Learning Environments Into Flexible, Active Learning Classrooms von Eickholt, Jesse, Johnson, Matthew R., Seeling, Patrick

“… Contribution: Practical active learning stations (PALSs)-equipped classrooms function similar to prototypical active learning classrooms (ALCs). They support …”
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Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control von Fasel, U, Kutz, J N, Brunton, B W, Brunton, S L

“… Sparse model identification enables the discovery of nonlinear dynamical systems purely from data; however, this approach is sensitive to noise, especially in …”
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