Branch merging on continuum trees with applications to regenerative tree growth

We introduce a family of branch merging operations on continuum trees and show that Ford CRTs are distributionally invariant. This operation is new even in the special case of the Brownian CRT, which we explore in more detail. The operations are based on spinal decompositions and a regenerativity preserving merging procedure of $(\alpha, \theta)$-strings of beads, that is, random intervals $[0, L_{\alpha, \theta}]$ equipped with a random discrete measure $dL^{-1}$ arising in the limit of ordered $(\alpha, \theta)$-Chinese restaurant processes as introduced recently by Pitman and Winkel. Indeed, we iterate the branch merging operation recursively and give an alternative approach to the leaf embedding problem on Ford CRTs related to $(\alpha, 2-\alpha)$-regenerative tree growth processes.Comment: 40 pages, 5 figure

Decision Stream: Cultivating Deep Decision Trees

Various modifications of decision trees have been extensively used during the past years due to their high efficiency and interpretability. Tree node splitting based on relevant feature selection is a key step of decision tree learning, at the same time being their major shortcoming: the recursive nodes partitioning leads to geometric reduction of data quantity in the leaf nodes, which causes an excessive model complexity and data overfitting. In this paper, we present a novel architecture - a Decision Stream, - aimed to overcome this problem. Instead of building a tree structure during the learning process, we propose merging nodes from different branches based on their similarity that is estimated with two-sample test statistics, which leads to generation of a deep directed acyclic graph of decision rules that can consist of hundreds of levels. To evaluate the proposed solution, we test it on several common machine learning problems - credit scoring, twitter sentiment analysis, aircraft flight control, MNIST and CIFAR image classification, synthetic data classification and regression. Our experimental results reveal that the proposed approach significantly outperforms the standard decision tree learning methods on both regression and classification tasks, yielding a prediction error decrease up to 35%

When a quantum measurement can be implemented locally ... and when it cannot

Local operations on subsystems and classical communication between parties (LOCC) constitute the most general protocols available on spatially separated quantum systems. Every LOCC protocol implements a separable generalized measurement -- a complete measurement for which every outcome corresponds to a tensor product of operators on individual subsystems -- but it is known that there exist separable measurements that cannot be implemented by LOCC. A longstanding problem in quantum information theory is to understand the difference between LOCC and the full set of separable measurements. In this paper, we show how to construct an LOCC protocol to implement an arbitrary separable measurement, except that with those measurements for which no LOCC protocol exists, the method shows explicitly that this is the case.Comment: 21 pages, 7 figures. Extensively revised to include details of all arguments, explicitly proving all results in full rigor. Version 3 has sections reordered and other restructuring, but otherwise contains the same discussion as version

Evaluating Semi-Analytic Halo Merging Histories

We evaluate the accuracy of semi-analytic merger-trees by comparing them with the merging histories of dark-matter halos in N-body simulations, focusing on the joint distribution of the number of progenitors and their masses. We first confirm that the halo mass function as predicted directly by the Press-Schechter (PS) model deviates from the simulations by up to 50% depending on the mass scale and redshift, while the means of the projected distributions of progenitor number and mass for a halo of a given mass are more accurately predicted by the Extended PS model. We then use the full merger trees to study the joint distribution as a function of redshift and parent-halo mass. We find that while the deviation of the mean quantities due to the inaccuracy of the Extended PS model partly propagates into the higher moments of the distribution, the merger-tree procedure does not introduce a significant additional source of error. In particular, certain properties of the merging history such as the mass ratio of the progenitors and the total accretion rate are reproduced quite accurately for galaxy sized halos (\sim 10^{12}\msun), and less so for larger masses. We conclude that although there could be $\sim 50$ deviations in the absolute numbers and masses of progenitors and in the higher order moment of these distributions, the relative properties of progenitors for a given halo are reproduced fairly well by the merger trees. They can thus provide a useful framework for modelling galaxy formation once the above-mentioned limitations are taken into account.Comment: 10 pages including 9 figures, submitted to MNRA