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大规模学习-挑战

Large Scale Learning - Challenge
课程网址: http://videolectures.net/icml08_sonnenburg_lsl/  
主讲教师: Vojtech Franc; Sören Sonnenburg
开课单位: 机器学习与智能数据分析小组
开课时间: 2008-09-01
课程语种: 英语
中文简介:
随着过去几十年计算能力、存储容量和网络带宽的显著增加, 不断增长的数据集被收集到生物信息学 (拼接站点、基因边界等)、it 安全 (网络流量) 或文本分类 (垃圾邮件与非垃圾邮件), 仅举几例。虽然数据大小的增长将计算方法作为处理数据的唯一可行方法, 但它对 ml 方法提出了新的挑战。 本研讨会关注的是现有 ml 方法在计算、内存或通信资源方面的可伸缩性和效率, 例如, 由于算法复杂性高、数据集的大小或维度以及分布式分辨率和通信成本之间的权衡。
课程简介: With the exceptional increase in computing power, storage capacity and network bandwidth of the past decades, ever growing datasets are collected in fields such as bioinformatics (Splice Sites, Gene Boundaries, etc), IT-security (Network traffic) or Text-Classification (Spam vs. Non-Spam), to name but a few. While the data size growth leaves computational methods as the only viable way of dealing with data, it poses new challenges to ML methods. This workshop is concerned with the scalability and efficiency of existing ML approaches with respect to computational, memory or communication resources, e.g. resulting from a high algorithmic complexity, from the size or dimensionality of the data set, and from the trade-off between distributed resolution and communication costs.
关 键 词: 网络流量; 文本分类; 数据集; 线性支持向量机的轨道
课程来源: 视频讲座网
最后编审: 2020-06-23:liqy
阅读次数: 35