Algorithms to find the first vertex in large random trees
Thursday 26 March 2014, 14h30, bât 660, Claude Shannon
Abstract : We discuss algorithms to find the first vertex in large random trees generated by either the uniform attachment or preferential attachment model. We require the algorithm to output a set of K vertices, such that, with probability at least 1 − ε, the first vertex is in this set. We show that for any ε, there exist such algorithms with K independent of the size of the tree. The talk is based on joint work with Seb Bubeck and Luc Devroye.
Gábor Lugosi is an ICREA Research Professor at the Department of Economics and Business at Pompeu Fabra University.
His research has mostly focused on mathematical aspects of machine learning including classification, density estimation, regression, but also clustering and data compression, ranking, and sequential prediction. He is also interested in concentration inequalities and understanding the behavior of large random structures such as random graphs and networks.
He has co-authored four research monographs ; one on classification (published by Springer in 1996), one on density estimation (also Spinger, 2001a) , one on sequential prediction (Cambridge University Press, 2006), and one on concentration inequalities (Oxford University Press, 2013).
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