J. Pazzani, "Active learning using on-line algorithms," Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 850-858, 2011Nguyen, H.T., and Smeulders, A. Active Learning Using Pre-clustering. In Proc. Int'l Conf. on Machine Learning (...
The idea to combine clustering and active learning has ap- peared in previous work. In (McCallum & Nigam, 1998), a naive Bayes classifier is trained over both labeled and unlabeled data using an EM algorithm. Under the con- dition that the overwhelming majority of the data is un- ...
During the active learning process, the clustering is adjusted using the coarse-to-fine strategy in order to balance between the advantage of large clusters and the accuracy of the data representation. The results of experiments in image databases show a better performance of our algorithm compared...
Smeulders Active learning using pre-clustering Proceedings of the Twenty-First International Conference on Machine Learning ICML ’04, ACM Press (2004), p. 79, 10.1145/1015330.1015349 Google Scholar 105 I. Dagan, S.P. Engelson Committee-based sampling for training probabilistic classifiers Proceedings...
Smeulders, "Active Learning Using Pre-clustering," in International Conference on Machine Learning, 2004, 79. Deep Active Learning for Computer Vision: Past and Future 35 [78] N. Ostapuk, J. Yang, and P. Cudré-Mauroux, "Activelink: Deep Active Learning for Link Prediction in Knowledge ...
文献“Active Learning using a Variational Dirichlet Processing model for pre-clustering and ...
Generally, data is available abundantly in unlabeled form, and its annotation requires some cost. The labeling, as well as learning cost, can be minimized
Robert Munro Monarch, Human-in-the-Loop Machine Learning: Active learning and annotation for human-centered AI, Manning, Aug. 2021, ISBN 9781638351030, p. 424. Google Scholar [27] Hieu Nguyen, Arnold Smeulders Active learning using pre-clustering ICML (2004), 10.1145/1015330.1015349 Google Scholar...
文献“Active Learning using a Variational Dirichlet Processing model for pre-clustering and classification of underwater stereo imagery(2011)”提出了一种利用预聚类协助选择代表性样例的主动学习方法; 文献“Dual strategy active learning(2007)”利用样例的不确定性及其先验分布密度进行样例选择以获取优质样例; 文...
clusters are appropriate for a specific active learning problem. Secondly, the clustering methods perform poorly when the data have no clear cluster structure, leading to inaccurate density estimation. Figure3illustrates the importance of cluster structure. The clustering algorithm works well when there ...