图 书 馆开课单位--国立高等电信学校
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1Massive Online Analysis, a Framework for Stream Classification and Clustering[海量在线分析，一种流分类和聚类的框架]
Albert Bifet(国立高等电信学校) Massive Online Analysis, a Framework for Stream Classification and Clustering
热度：69
Albert Bifet(国立高等电信学校) Massive Online Analysis, a Framework for Stream Classification and Clustering
热度：69
2Information Complexity in Bandit Subset Selection[Bandit子集选择中的信息复杂性]
Emilie Kaufmann(国立高等电信学校) We consider the problem of efficiently exploring the arms of a stochastic bandit to identify the best subset. Under the PAC and the fixed-budget formu...
热度：53
Emilie Kaufmann(国立高等电信学校) We consider the problem of efficiently exploring the arms of a stochastic bandit to identify the best subset. Under the PAC and the fixed-budget formu...
热度：53
3MOA Concept Drift Active Learning Strategies for Streaming Data[MOA概念漂移用于数据流的主动学习策略]
Albert Bifet(国立高等电信学校) We present a framework for active learning on evolving data streams, as an extension to the MOA system. In learning to classify streaming data, obtain...
热度：89
Albert Bifet(国立高等电信学校) We present a framework for active learning on evolving data streams, as an extension to the MOA system. In learning to classify streaming data, obtain...
热度：89
4Detecting Sentiment Change in Twitter Streaming Data[检测twitter流数据中的情绪变化]
Albert Bifet(国立高等电信学校) MOA-TweetReader is a real-time system to read tweets in real time, to detect changes, and to find the terms whose frequency changed. Twitter is a micr...
热度：34
Albert Bifet(国立高等电信学校) MOA-TweetReader is a real-time system to read tweets in real time, to detect changes, and to find the terms whose frequency changed. Twitter is a micr...
热度：34
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