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From the existence of an efficient quantum algorithm for factoring, it is likely that quantum computation is intrinsically more powerful than classical computation. At present, the best upper bound known for the power of quantum computation…

Quantum Physics · Physics 2015-09-14 Ciarán M. Lee , Jonathan Barrett

One of the main virtues of trees is to represent formal solutions of various functional equations which can be cast in the form of fixed point problems. Basic examples include differential equations and functional (Lagrange) inversion in…

Combinatorics · Mathematics 2013-02-12 Florent Hivert , Jean-Christophe Novelli , Jean-Yves Thibon

We show that if \kappa\ is a weakly compact cardinal then the embeddability relation on (generalized) trees of size \kappa\ is invariantly universal. This means that for every analytic quasi-order R on the generalized Cantor space 2^\kappa\…

Logic · Mathematics 2013-06-28 Luca Motto Ros

The Steiner Tree problem is a classical problem in combinatorial optimization: the goal is to connect a set $T$ of terminals in a graph $G$ by a tree of minimum size. Karpinski and Zelikovsky (1996) studied the $\delta$-dense version of…

Data Structures and Algorithms · Computer Science 2020-04-30 Marek Karpinski , Mateusz Lewandowski , Syed Mohammad Meesum , Matthias Mnich

Specifying a computational problem requires fixing encodings for input and output: encoding graphs as adjacency matrices, characters as integers, integers as bit strings, and vice versa. For such discrete data, the actual encoding is…

Logic · Mathematics 2021-08-25 Donghyun Lim , Martin Ziegler

The data arrangement problem on regular trees (DAPT) consists in assigning the vertices of a given graph G to the leaves of a d-regular tree T such that the sum of the pairwise distances of all pairs of leaves in T which correspond to edges…

Optimization and Control · Mathematics 2013-04-23 Eranda Cela , Rostislav Stanek

The hierarchical and recursive expressive capability of rooted trees is applicable to represent statistical models in various areas, such as data compression, image processing, and machine learning. On the other hand, such hierarchical…

Machine Learning · Computer Science 2022-01-25 Yuta Nakahara , Shota Saito , Akira Kamatsuka , Toshiyasu Matsushima

The largest common embeddable subtree problem asks for the largest possible tree embeddable into two input trees and generalizes the classical maximum common subtree problem. Several variants of the problem in labeled and unlabeled rooted…

Data Structures and Algorithms · Computer Science 2018-05-03 Andre Droschinsky , Nils M. Kriege , Petra Mutzel

We are concerned with the problem of witnessing the Baire property of the Borel and the projective sets (assuming determinacy) through a sufficiently definable function in the codes. We prove that in the case of projective sets it is…

Logic · Mathematics 2017-07-25 Vassilios Gregoriades

The unwavering success of deep learning in the past decade led to the increasing prevalence of deep learning methods in various application fields. However, the downsides of deep learning, most prominently its lack of trustworthiness, may…

Machine Learning · Computer Science 2024-08-13 Holger Boche , Vit Fojtik , Adalbert Fono , Gitta Kutyniok

We prove several new tight distributed lower bounds for classic symmetry breaking graph problems. As a basic tool, we first provide a new insightful proof that any deterministic distributed algorithm that computes a $\Delta$-coloring on…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-06-03 Alkida Balliu , Sebastian Brandt , Fabian Kuhn , Dennis Olivetti

We propose an algorithm named best-scored random forest for binary classification problems. The terminology "best-scored" means to select the one with the best empirical performance out of a certain number of purely random tree candidates…

Machine Learning · Statistics 2019-05-28 Hanyuan Hang , Xiaoyu Liu , Ingo Steinwart

When considering the number of subtrees of trees, the extremal structures which maximize this number among binary trees and trees with a given maximum degree lead to some interesting facts that correlate to other graphical indices in…

Combinatorics · Mathematics 2012-10-11 Xiu-Mei Zhang , Xiao-Dong Zhang , Daniel Gray , Hua Wang

We study restricted computation models related to the Tree Evaluation Problem}. The TEP was introduced in earlier work as a simple candidate for the (*very*) long term goal of separating L and LogDCFL. The input to the problem is a rooted,…

Computational Complexity · Computer Science 2010-02-26 Dustin Wehr

An archetypal problem discussed in computer science is the problem of searching for a given number in a given set of numbers. Other than sequential search, the classic solution is to sort the list of numbers and then apply binary search.…

Computational Complexity · Computer Science 2015-03-20 Philon Nguyen

This paper shows that decision trees constructed with Classification and Regression Trees (CART) and C4.5 methodology are consistent for regression and classification tasks, even when the number of predictor variables grows…

Machine Learning · Statistics 2023-11-15 Jason M. Klusowski , Peter M. Tian

We provide a gentle introduction, aimed at non-experts, to Borel combinatorics that studies definable graphs on topological spaces. This is an emerging field on the borderline between combinatorics and descriptive set theory with deep…

Combinatorics · Mathematics 2021-01-19 Oleg Pikhurko

This paper is aimed to investigate some computational aspects of different isoperimetric problems on weighted trees. In this regard, we consider different connectivity parameters called {\it minimum normalized cuts}/{\it isoperimteric…

Computational Complexity · Computer Science 2010-09-06 Amir Daneshgar , Ramin Javadi

Recent results show that a constraint satisfaction problem (CSP) defined over rational numbers with their natural ordering has a solution if and only if it has a definable solution. The proof uses advanced results from topology and modern…

Logic in Computer Science · Computer Science 2020-03-31 Michał R. Przybyłek

Machine learning methods for estimating treatment effect heterogeneity promise greater flexibility than existing methods that test a few pre-specified hypotheses. However, one problem these methods can have is that it can be challenging to…

Econometrics · Economics 2024-08-05 Patrick Rehill