We focus on the pool-based active learning, which is one of the most popular branches of active learning. The proposed quantum active learning algorithm can achieve quadratic speedup over the classical pool-based active learning.doi:10.1007/s11128-019-2460-x...
libactis a Python package designed to make active learning easier for real-world users. The package not only implements several popular active learning strategies, but also features theactive-learning-by-learningmeta-algorithm that assists the users to automatically select the best strategy on the fl...
首先,作者们考虑了 pool-based batch active learning for noisy linear models。(即 f∗ 是一个线性模型,而且每一个数据点的 label 都是带噪声的),并提出了一套非常高效的算法,该算法仍然是基于 pseudo-label,即在不知道一个数据点的 label之前用当前模型给它安排的一个假label,在作者们的新算法中,每一个...
Employing EM and Pool-Based Active Learning for Text Classification Andrew McCallumKamal Nigam Just Research and Carnegie Mellon University Text Active Learning Many applications Scenario: ask for labels of a few documents While learning: –Learner carefully selects unlabeled document –Trainer provides la...
learning require less than two-thirds as many labeled training examples as previous QBC approaches, and that the combination of EM and active learning requires only slightly more than half as many labeled training examples to achieve the same accuracy as either the improved active learning or EM ...
摘要: CiteSeerX - Scientific documents that cite the following paper: Employing EM in Pool-Based Active Learning for Text Classification会议名称: Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), Madison, Wisconsin, USA, July 24-27, 1998 ...
A. Self-supervised deep-learning encodes high-resolution features of protein subcellular localization. Preprint at bioRxiv https://doi.org/10.1101/2021.03.29.437595 (2021). Strezoska, Ž. et al. High-content analysis screening for cell cycle regulators using arrayed synthetic crRNA libraries. J. ...
Study Selection and Data AbstractionStudies involving ART-naive participants initiating NNRTI-based regimens were included. Participants were included if all drugs in their ART regimen were fully active by standard HIV drug resistance testing. Cox proportional hazard models using pooled patient-level data...
Utilizing deep learning, we detect the characteristics of the melt pool, and employ a computer vision algorithm to determine the upper and lower contact angles for force balance analysis. This enables us to predict the state of the melt pool (normal or otherwise) and promptly feed the results ...
Two approaches are presented for this task: active classifier and weighted classifiers methods. Then the true labels are revealed and the pool is updated at the end of the batch. Updating the pool is done using one of the following methods: exact Bayesian, Bayesian and Heuristic. As the ...