The classification of genomic and proteomic data in extremely high dimensional datasets is a wellknown problem which requires appropriate classification techniques. Classification methods are usually combined with gene selection techniques to provide optimal classification conditions—i.e. a lower dimensional classification environment. Another reason for reducing the dimensionality of such data...

We study depth properties of a general class of random recursive trees where each node n attaches to the random node !nXn" and X0, . . . , Xn is a sequence of i.i.d. random variables taking values in [0, 1). We call such trees scaled attachment random recursive trees (SARRT). We prove that the height Hn of a SARRT is asymptotically given by Hn ∼ αmax log n where αmax is a constant depending onl...

Fix a Pareto optimal, strategy proof and non-bossy deterministic matching mechanism and define a random matching mechanism by assigning agents to the roles in the mechanism via a uniform lottery. Given a profile of preferences, the lottery over outcomes that arises under the random matching mechanism is identical to the lottery that arises under random serial dictatorship, where the order of di...

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Simple families of increasing trees have been introduced by Bergeron, Flajolet and Salvy. They include random binary search trees, random recursive trees and random plane-oriented recursive trees (PORTs) as important special cases. In this paper, we investigate the number of subtrees of size k on the fringe of some classes of increasing trees, namely generalized PORTs and d-ary increasing trees...

In this paper a simple and efficient framework for single human action recognition is proposed. In two parallel processing streams, motion information and static object appearances are gathered by introducing a frame-by-frame learning approach. For each processing stream a Random Forest classifier is separately learned. The final decision is determined by combining both probability functions. T...

The diagnosis of cancer type based on microarray data offers hope that cancer classification can be highly accurate for clinicians to choose the most appropriate forms of treatment with it. Due to several inherent characteristics associated with microarray data, accurate diagnosis has been an active research topic attracting tremendous research interests in machine learning community. In this p...

For the case of smooth concave exchange economies, we provide a characterization of the inner core as the set of feasible allocations such that no coalition can improve on it, even if coalitions are allowed to use some random plans. For the case of compactly generated games, we discuss Myerson’s definition of the inner core, and we characterize it using lexicographic utility weight systems.  2...

We prove the exact asymptotic 1 − Θ( 1 √ n ) for the probability that the underlying graph of a random mapping of n elements possesses a unique highest tree. The property of having a unique highest tree turned out to be crucial in the solution of the famous Road Coloring Problem [7] as well as in the proof of the author’s result about the probability of being synchronizable for a random automat...