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Learning with hidden variables is a central challenge in probabilistic graphical models that has important implications for many real-life problems. The classical approach is using the Expectation Maximization (EM) algorithm. This…

Machine Learning · Computer Science 2012-12-12 Gal Elidan , Nir Friedman

A critical branching process $\left\{Z_{k},k=0,1,2,...\right\} $ in a random environment generated by a sequence of independent and identically distributed random reproduction laws is considered.\ Let $Z_{p,n}$ be the number of particles at…

Probability · Mathematics 2016-08-30 V. A. Vatutin , E. E. Dyakonova

Chv\'{a}tal and Klincsek (1980) gave an $O(n^3)$-time algorithm for the problem of finding a maximum-cardinality convex subset of an arbitrary given set $P$ of $n$ points in the plane. This paper examines a generalization of the problem,…

Computational Geometry · Computer Science 2021-08-31 Stephane Durocher , J. Mark Keil , Saeed Mehrabi , Debajyoti Mondal

In this paper, we study the quantity of computational resources (state machine states and/or probabilistic transition precision) needed to solve specific problems in a single hop network where nodes communicate using only beeps. We begin by…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-08-18 Seth Gilbert , Calvin Newport

We propose an efficient algorithm for approximate computation of the profile maximum likelihood (PML), a variant of maximum likelihood maximizing the probability of observing a sufficient statistic rather than the empirical sample. The PML…

Machine Learning · Computer Science 2017-12-21 Dmitri S. Pavlichin , Jiantao Jiao , Tsachy Weissman

We present a new variant of the secretary problem. Let $A$ be a totally ordered set of $n$ \emph{applicants}. Given $P\subseteq A$ and $x\in A$, let $rr(P,x)=\vert\{z\in P \mid z\leq x\}\vert\mbox{ }$ be the \emph{relative rank of} $x$…

Probability · Mathematics 2023-07-10 Josef Rukavicka

In this paper we study the strict majority bootstrap percolation process on graphs. Vertices may be active or passive. Initially, active vertices are chosen independently with probability p. Each passive vertex becomes active if at least…

Social and Information Networks · Computer Science 2013-11-21 Marcos Kiwi , Pablo Moisset de Espanés , Ivan Rapaport , Sergio Rica , Guillaume Theyssier

In statistical mechanics, the generally called Stirling approximation is actually an approximation of Stirling's formula. In this article, it is shown that the term that is dropped is in fact the one that takes fluctuations into account.…

Classical Physics · Physics 2023-11-01 Didier Lairez

We propose a new approach for deriving probabilistic inequalities based on bounding likelihood ratios. We demonstrate that this approach is more general and powerful than the classical method frequently used for deriving concentration…

Probability · Mathematics 2013-11-21 Xinjia Chen

I present a single algorithm which solves the clique problems, "What is the largest size clique?", "What are all the maximal cliques?" and the decision problem, "Does a clique of size k exist?" for any given graph in polynomial time. The…

Data Structures and Algorithms · Computer Science 2015-03-17 Michael LaPlante

We are interested in bounding probabilities of rare events in the context of computer experiments. These rare events depend on the output of a physical model with random input variables. Since the model is only known through an expensive…

Computation · Statistics 2012-03-21 Yves Auffray , Pierre Barbillon , Jean-Michel Marin

A problem dating back to Boole [Laws of Thought, Walton & Maberly,1854] is what can be computed about the probability of a finite union of events when given as input the probabilities of intersections of some of the events. The modern…

Computational Complexity · Computer Science 2026-05-06 Petteri Kaski , Heikki Mannila , Chandra Kanta Mohapatra

In this paper we consider the palindromes that can be formed by taking unordered sets of $n$ elements from an alphabet of $b$ letters. In particular, we seek to find the probability that given a random member of this space we are able to…

Combinatorics · Mathematics 2016-04-11 Alexander Burlton

Finding the most powerful node in a dynamic random network, the largest set in a partition-valued stochastic process, or the largest family in an evolving population at a given time, can be a very difficult problem. This is particularly the…

Probability · Mathematics 2020-09-09 Cécile Mailler , Peter Mörters , Anna Senkevich

The halting problem is undecidable --- but can it be solved for "most" inputs? This natural question was considered in a number of papers, in different settings. We revisit their results and show that most of them can be easily proven in a…

Logic · Mathematics 2017-01-11 Laurent Bienvenu , Damien Desfontaines , Alexander Shen

The problem we are considering is the following. A colorblind player is given a set $B = \{b_1,b_2,...,b_N\}$ of $N$ colored balls. He knows that each ball is colored either red or green, and that there are less green balls (this will be…

A family of sets is called $r$-\emph{cover free} if no set in the family is contained in the union of $r$ (or less) other sets in the family. A $1$-cover free family is simply an antichain with respect to set inclusion. Thus, Sperner's…

Combinatorics · Mathematics 2020-11-10 Noga Alon , Shoni Gilboa , Shay Gueron

We investigate a class of chance-constrained combinatorial optimization problems. Given a pre-specified risk level $\epsilon \in [0,1]$, the chance-constrained program aims to find the minimum cost selection of a vector of binary decisions…

Optimization and Control · Mathematics 2020-06-02 Hao-Hsiang Wu , Simge Kucukyavuz

This paper mainly addresses the optimization of $p$-th moment of $\mathbb{R}^n$-valued random variable. Through an ingenious approximation mechanism, one transforms the maximization problem into a sequence of minimization problems, which…

Optimization and Control · Mathematics 2016-07-26 Xiaojun Lu , Yanhua Wu

The dynamics of a population exhibiting exponential growth can be modelled as a birth-death process, which naturally captures the stochastic variation in population size over time. In this article, we consider a supercritical birth-death…

Populations and Evolution · Quantitative Biology 2020-05-07 Anastasia Ignatieva , Jotun Hein , Paul A. Jenkins
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