Nov 11, 2020 · In this paper, we propose an unsupervised active learning framework, called Robust Grouping Active Learning (RGAL), to achieve this goal. The ...
In this paper, we propose a robust grouping active learning algorithm, called RGAL, by taking into account that data are often drawn from multiple low- ...
Researchr is a web site for finding, collecting, sharing, and reviewing scientific publications, for researchers by researchers. Sign up for an account to ...
People also ask
What are the principles of active learning?
What is the definition of active learning in education?
How do you encourage active learning?
How can students co-create an active learning environment?
The current paper proposes two novel approaches to counteract the effects of sampling bias: semi-supervised learning, and discriminative classification models.
Cluster analysis is an unsupervised learning technique which identifies groups ... ture and active learning (based on majority voting and the robust ensemble.
Sep 22, 2022 · We introduce a novel learning framework, Fair Robust Active Learning (FRAL), generalizing conventional active learning to fair and adversarial robust scenarios.
Aug 11, 2024 · Learning from noisy labels (LNL) is a chal- lenge that arises in many real-world scenarios where collected training data can contain in-.
Jul 28, 2022 · Predicting implementation of active learning by tenure-track teaching faculty using robust cluster analysis
Active learning methods ask students to engage in their learning by thinking, discussing, investigating, and creating.
2020b. On Robust Grouping Active Learning. IEEE Transactions on Emerging Topics in Computational Intelligence . Lu, C.; Min, H.