With the development of new technologies such as big data, cloud computing, and the
Internet of Things, network attack technology is constantly evolving and upgrading, and …

Semi-supervised clustering is a new learning method which combines semi-supervised
learning (SSL) and cluster analysis. It is widely valued and applied to machine learning …

实体关系抽取作为信息抽取, 自然语言理解, 信息检索等领域的核心任务和重要环节,
能够从文本中抽取实体对间的语义关系. 近年来, 深度学习在联合学习, 远程监督等方面上的应用 …

Most existing hydrologic models and machine learning models failed to perform well on
runoff prediction in data scarce regions. As an alternative to this, the Long Short-Term …

Self-training is a commonly semi-supervised learning Algorithm framework. How to select
the high-confidence samples is a crucial step for algorithms based on self-training …

摘要高光谱遥感影像分类通常基于地物光谱特征, 但影像中同时还存在丰富的空间信息.
空间信息的有效利用能显著提高图像分类效果. 因其具有的特殊结构, 卷积神经网络(CNN) …

深度学习在人工智能领域已经取得了非常优秀的成就, 在有监督识别任务中,
使用深度学习算法训练海量的带标签数据, 可以达到前所未有的识别精确度. 但是 …

Fraudulent user detection is a crucial issue in financial risk management. Due to the lack of
labeled data and the reliability of labeling, label propagation algorithms (LPA) are effective …

Intrusion detection plays a very important role in the field of network security. In order to
improve the intrusion detection rate, intrusion detection algorithms based traditional …

Tri-training expands the training set by adding pseudo-labels to unlabeled data, which
effectively improves the generalization ability of the classifier, but it is easy to mislabel …