Predicting a switching sequence of graph labelings

M. Herbster, Stephen Pasteris, M. Pontil
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引用次数: 15

Abstract

We study the problem of predicting online the labeling of a graph. We consider a novel setting for this problem in which, in addition to observing vertices and labels on the graph, we also observe a sequence of just vertices on a second graph. A latent labeling of the second graph selects one of K labelings to be active on the first graph. We propose a polynomial time algorithm for online prediction in this setting and derive a mistake bound for the algorithm. The bound is controlled by the geometric cut of the observed and latent labelings, as well as the resistance diameters of the graphs. When specialized to multitask prediction and online switching problems the bound gives new and sharper results under certain conditions.
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预测图标记的切换顺序
我们研究了在线预测图的标注问题。我们考虑了这个问题的一种新设置,除了观察图上的顶点和标签外,我们还观察了另一个图上的一个顶点序列。第二个图的潜在标记从K个标记中选择一个在第一个图上活动。在这种情况下,我们提出了一种多项式时间的在线预测算法,并推导了该算法的错误界。边界由观察到的和潜在的标记的几何切割以及图的阻力直径控制。当专门用于多任务预测和在线切换问题时,该界在一定条件下给出了新的、更清晰的结果。
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