Semisupervised incremental learning is the task of classifying data streams with partially
labeled data when annotation information is difficult to obtain. Besides the sequential …

Incremental learning is one of the research hotspots in machine learning. In this paper, we
view the complex changes of data as three changes that are the change of sample, the …

相比于传统的雷达对抗系统, 认知雷达对抗引入了闭环行为学习过程, 使得干扰方可以通过对
雷达信号进行状态辨识, 进而进行干扰效果评估, 经过自主学习优化干扰策略 …

出使用模拟切削算法的SVM 增量学习机制. 模拟切削算法在核函数映射的特征空间中计算每个
样本的预期贡献率, 仅选取预期贡献率较高的样本参与SVM 增量学习, 有效解决传统SVM …

针对P2P 流媒体流量识别中的类增量学习问题, 提出一种基于" 一对一" 支持向量机多分类器的
类增量学习算法CIOOL. 充分利用原有多分类器知识, 在不打破原有分类器体系的前提下加入新 …

Neste trabalho a detecção de novidade é tratada como o problema de identificação de
conceitos emergentes em dados que podem ser apresentados em um fluxo contínuo …

With various remote sensing technologies to aid Earth Observation, radar-based imaging is
one of them gaining major interests due to advances in its imaging techniques in form of syn …

In this paper, we introduce dynamic and scalable Synthetic Aperture Radar (SAR) terrain
classification based on the Collective Network of Binary Classifiers (CNBC). The CNBC …

支持向量机(SVM) 主动学习模型能够很好地解决入侵检测系统的小样本学习的问题,
提高入侵检测系统中分类器的性能. 针对SVM 主动学习模型对于构建初始训练集具有随机性 …

Multimedia collections are growing in a tremendous pace as the modus operandi for
information creation, exchange, and storage in our modern era. This creates an urgent need …