Lipschitz embeddings of random sequences

We develop a new multi-scale framework flexible enough to solve a number of problems involving embedding random sequences into random sequences. Grimmett et al. (Random Str Algorithm 37(1):85–99, 2010) asked whether there exists an increasing \(M\)-Lipschitz embedding from one i.i.d. Bernoulli sequence into an independent copy with positive probability. We give a positive answer for large enough \(M\). A closely related problem is to show that two independent Poisson processes on \(\mathbb R \) are roughly isometric (or quasi-isometric). Our approach also applies in this case answering a conjecture of Szegedy and of Peled (Ann Appl Probab 20:462–494, 2010). Our theorem also gives a new proof to Winkler’s compatible sequences problem. Our approach does not explicitly depend on the particular geometry of the problems and we believe it will be applicable to a range of multi-scale and random embedding problems.     

Low distortion euclidean embeddings of trees

We consider the problem of embedding a certain finite metric space to the Euclidean space, trying to keep the bi-Lipschitz constant as small as possible. We introduce the notationc ₂(X, d) for the least distortion with which the metric space (X, d) may be embedded in a Euclidean space. It is known that if (X, d) is a metric space withn points, thenc ₂(X, d)≤0(logn) and the bound is tight. LetT be a tree withn vertices, andd be the metric induced by it. We show thatc ₂(T, d)≤0(log logn), that is we provide an embeddingf of its vertices to the Euclidean space, such thatd(x, y)≤‖f(x)−f(y) ‖≤c log lognd(x, y) for some constantc. Supported in part by grants from the Israeli Academy of Sciences and the US-Israel Binational Science Foundation. Supported in part by NSF under grants CCR-9215293 and by DIMACS, which is supported by NSF grant STC-91-19999 and by the New Jersey Commission on Science and Technology.     

Global optimization using random embeddings

Mathematical Programming - We propose a random-subspace algorithmic framework for global optimization of Lipschitz-continuous objectives, and analyse its convergence using novel tools from conic...     

Polynomial area bounds for MST embeddings of trees

In their seminal paper on geometric minimum spanning trees, Monma and Suri (1992) [31] showed how to embed any tree of maximum degree 5 as a minimum spanning tree in the Euclidean plane. The embeddings provided by their algorithm require area O(n²²)×O(n²²) and the authors conjectured that an improvement below cn×cn is not possible, for some constant c>0. In this paper, we show how to construct MST embeddings of arbitrary trees of maximum degree 3 and 4 within polynomial area.     

Note on the heights of random recursive trees and random m-ary search trees

A process of growing a random recursive tree T_n is studied. The sequence {T_n} is shown to be a sequence of “snapshots” of a Crump–Mode branching process. This connection and a theorem by Kingman are used to show quickly that the height of T_n is asymptotic, with probability one, to c log n. In particular, c = e = 2.718 … for the uniform recursive tree, and c = (2γ)^?1, where γe^1+γ = 1, for the ordered recursive tree. An analogous reduction provides a short proof of Devroye's limit law for the height of a random m-ary search tree. We show finally a close connection between another Devroye's result, on the height of a random union-find tree, and our theorem on the height of the uniform recursive tree. © 1994 John Wiley & Sons, Inc.     

On random cartesian trees

Cartesian trees are binary search trees in which the nodes exhibit the heap property according to a second (priority) key. If the search key and the priority key are independent, and the trees is built based on n independent copies, Cartesian trees basically behave like ordinary random binary search trees. In this article, we analyze the expected behavior when the keys are dependent: in most cases, the expected search, insertion, and deletion times are Φ(√n). We indicate how these results can be used in the analysis of divide-and-conguer algorithms for maximal vectors and convex hulls. Finally, we look at distributions for which the expected time per operation grows like n^a for a ?[1/2, 1]. © 1994 John Wiley & Sons, Inc.     

Limits of random trees

Local convergence of bounded degree graphs was introduced by Benjamini and Schramm [2]. This result was extended further by Lyons [4] to bounded average degree graphs. In this paper, we study the convergence of a random tree sequence (T _n ), where the probability of a given tree T is proportional to $\prod_{v_{i}\in V(T)}d(v_{i})!$ . We show that this sequence is convergent and describe the limit object, which is a random infinite rooted tree.     

Pathwidth of Planar and Line Graphs

 We prove that for every 2-connected planar graph the pathwidth of its geometric dual is less than the pathwidth of its line graph. This implies that pathwidth(H)≤ pathwidth(H ^*)+1 for every planar triangulation H and leads us to a conjecture that pathwidth(G)≤pathwidth(G ^*)+1 for every 2-connected graph G. Received: May 8, 2001 Final version received: March 26, 2002 RID="*" ID="*" I acknowledge support by EC contract IST-1999-14186, Project ALCOM-FT (Algorithms and Complexity - Future Technologies) and support by the RFBR grant N01-01-00235. Acknowledgments. I am grateful to Petr Golovach, Roland Opfer and anonymous referee for their useful comments and suggestions.     

Two explicit Skorokhod embeddings for simple symmetric random walk

Motivated by problems in behavioural finance, we provide two explicit constructions of a randomized stopping time which embeds a given centred distribution $\mu$ on integers into a simple symmetric random walk in a uniformly integrable manner. Our first construction has a simple Markovian structure: at each step, we stop if an independent coin with a state-dependent bias returns tails. Our second construction is a discrete analogue of the celebrated Azéma–Yor solution and requires independent coin tosses only when excursions away from maximum breach predefined levels. Further, this construction maximizes the distribution of the stopped running maximum among all uniformly integrable embeddings of $\mu$.     

Counting trees with random walks

We give a simple proof of Tutte’s matrix-tree theorem, a well-known result providing a closed-form expression for the number of rooted spanning trees in a directed graph. Our proof stems from placing a random walk on a directed graph and then applying the Markov chain tree theorem to count trees. The connection between the two theorems is not new, but it appears that only one direction of the formal equivalence between them is readily available in the literature. The proof we now provide establishes the other direction. More generally, our approach is another example showing that random walks can serve as a powerful glue between graph theory and Markov chain theory, allowing formal statements from one side to be carried over to the other.     

A problem on random trees

The problem is considered of determining the distribution of the number of nodes in any given component of a forest obtained by removing edges from a random tree.     

Percolation on random recursive trees

We study Bernoulli bond percolation on a random recursive tree of size n with percolation parameter p(n) converging to 1 as n tends to infinity. The sizes of the percolation clusters are naturally stored in a tree structure. We prove convergence in distribution of this tree‐indexed process of cluster sizes to the genealogical tree of a continuous‐state branching process in discrete time. As a corollary we obtain the asymptotic sizes of the largest and next largest percolation clusters, extending thereby a recent work of Bertoin [5]. In a second part, we show that the same limit tree appears in the study of the tree components which emerge from a continuous‐time destruction of a random recursive tree. We comment on the connection to our first result on Bernoulli bond percolation. © 2015 Wiley Periodicals, Inc. Random Struct. Alg., 48, 655–680, 2016     

Multicolored trees in random graphs

We discuss the existence of multi-colored trees in randomly colored, random graphs. © 1994 John Wiley & Sons, Inc.     

On growing random binary trees

A sequence {T_n}_{n = 1}^∞ of nested binary trees generated by an infinite sequence of i.i.d. random variables is studied. Two absolute constants β₁,β₂ are shown to exist (0.37 < β₁ < 0.50, 3.58 < β₂ < 4.32), such that $\text{lim}\text{h}{}_{\mathrm{n}}\text{ln}\text{n = β}{}_1\text{,}\text{lim}\text{H}{}_{\mathrm{n}}\text{/}\text{ln}\text{n = β}{}_2$ with probability one; here h_n and H_n are respectively the lengths of the shortest and the longest branches of the tree T_n.     

A family of random trees with random edge lengths

We introduce a family of probability distributions on the space of trees with I labeled vertices and possibly extra unlabeled vertices of degree 3, whose edges have positive real lengths. Formulas for distributions of quantities such as degree sequence, shape, and total length are derived. An interpretation is given in terms of sampling from the inhomogeneous continuum random tree of Aldous and Pitman (1998). ©1999 John Wiley & Sons, Inc. Random Struct. Alg., 15, 176–195, 1999