Active learning with pre-clustering - Nguyen, Smeulders - 2004 () Citation Context ...ction is done by Equation 1. The error expectation for a given unlabeled point E[(ˆyi − yi) 2 | xi] in that equation is: k=1 E[(ˆyi − yi) 2 | xi] = (ˆyi − 1) 2 P(yi ...
Active learningClusteringUnsupervised feature learningActive learning is a type of semi-supervised learning in which the training algorithm is able to obtain the labels of a small portion of the unlabeled dataset by interacting with an external source (e.g. a human annotator). One strategy employed...
可是我们会发现，clustering这种硬性的限制很容易让sample聚集在cluster周围，降低多样性（如下图中间）。
the interaction with human. The clustering information is then useful for active learning in two ways. First, the rep- resentative samples located in center of clusters are more important than the other, and should be selected first in la- ...
clustering scRNA-seq data use an unsupervised learning strategy. Since the clustering step is separated from the cell annotation and labeling step, it is not uncommon for a totally exotic clustering with poor biological interpretability to be generated—a result generally undesired by biologists. To ...
The active learning loop can be used in a variety of machine learning applications such as classification, regression, clustering, anomaly detection, data cleaning, auto-mapping etc. Which method is best? There’s no one-size-fits-all answer to this question. Different methods will work better ...
We trained a Multi-layer Perceptron (MLP) classifier using the annotated representatives’ cells and used it to predict the cell types of the rest of the non-representative samples’ cells generated by the deep learning model. As shown in Fig. 2b, cell clustering remains intact in the semi-...
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...
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...
Selecting Influential Examples: Active Learning with Expected Model Output Changes Alexander Freytag , Erik Rodner , and Joachim Denzler Computer Vision Group, Friedrich Schiller University Jena, Germany {firstname.lastname}@uni-jena.de http://www.inf-cv.uni-jena.de Abstract. In this paper, we ...