图 书 馆开课单位--都灵理工大学
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2Identifying risks in datasets for automated decision–making[识别数据集中的风险以进行自动化决策]
Mariachiara Mecati(都灵理工大学) Identifying risks in datasets for automated decision–making
热度：62
Mariachiara Mecati(都灵理工大学) Identifying risks in datasets for automated decision–making
热度：62
3From clustering to algorithms[从聚类算法]
Riccardo Zecchina(都灵理工大学) In this talk we firstly provide a rigorous probabilistic proof of the clustering phenomenon taking place in the space of solution of random combinator...
热度：88
Riccardo Zecchina(都灵理工大学) In this talk we firstly provide a rigorous probabilistic proof of the clustering phenomenon taking place in the space of solution of random combinator...
热度：88
4Unified survey-belief propagation approach for satisfiability[统一调查信仰可满足性的传播方式]
Marco Pretti(都灵理工大学) In this talk I shall discuss a modified message-passing BP (Belief Propagation) procedure, which can be generally used to minimize variational Bethe f...
热度：72
Marco Pretti(都灵理工大学) In this talk I shall discuss a modified message-passing BP (Belief Propagation) procedure, which can be generally used to minimize variational Bethe f...
热度：72
5Cluster Variation Method: from statistical mechanics to message passing algorithms[集团变分法:从统计力学到消息传递算法]
Alessandro Pelizzola(都灵理工大学) The cluster variation method (CVM) is a hierarchy of approximate variational techniques for discrete (Ising--like) models in equilibrium statistical m...
热度：55
Alessandro Pelizzola(都灵理工大学) The cluster variation method (CVM) is a hierarchy of approximate variational techniques for discrete (Ising--like) models in equilibrium statistical m...
热度：55
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