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...

In this paper we describe our machine learning solution for the RecSys Challenge 2015. We have proposed a timeefficient two-stage cascaded classifier for the prediction of buy sessions and purchased items within such sessions. Based on the model, several interesting features found, and formation of our own test bed, we have achieved a reasonable score. Usage of Random Forests helps us to cope w...

The frequency and severity of forest fires, coupled with changes in spatial and temporal precipitation and temperature patterns, are likely to severely affect the characteristics of forest and permafrost patterns in boreal eco-regions. Forest fires, however, are also an ecological factor in how forest ecosystems form and function, as they affect the rate and characteristics of tree recruitment....

The last decade has witnessed a growing interest in random forest models which are recognized to exhibit good practical performance, especially in high-dimensional settings. On the theoretical side, however, their predictive power remains largely unexplained, thereby creating a gap between theory and practice. The aim of this paper is twofold. Firstly, we provide theoretical guarantees to link ...

We present a system for estimating location and orientation of a person’s head, from depth data acquired by a low quality device. Our approach is based on discriminative random regression forests: ensembles of random trees trained by splitting each node so as to simultaneously reduce the entropy of the class labels distribution and the variance of the head position and orientation. We evaluate ...

The formation and growth of atmospheric aerosol particles is considered using an exact discrete method with molecular resolution in size space. The method is immune to numerical diffusion problems that are a nuisance for typical simulation methods using a sectional representation for the particle size distribution. For condensational growth, a slight modification is proposed for the Fuchs-Sutug...