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It is a critical issue to compute the shortest paths between nodes in networks. Exact algorithms for shortest paths are usually inapplicable for large scale networks due to the high computational complexity. In this paper, we propose a…

Social and Information Networks · Computer Science 2015-06-29 Shi-nan Gong , Duan-bing Chen , Hui Gao , Guan-nan Wang , Liang-wei Wang

In this paper we consider the problem of locating a nonzero entry in a high-dimensional vector from possibly adaptive linear measurements. We consider a recursive bisection method which we dub the compressive binary search and show that it…

Information Theory · Computer Science 2012-06-01 Mark A. Davenport , Ery Arias-Castro

We propose a splitting algorithm for solving a system of composite monotone inclusions formulated in the form of the extended set of solutions in real Hilbert spaces. The resluting algorithm is a an extension of the algorithm in [4]. The…

Optimization and Control · Mathematics 2013-08-14 Dinh Dung , Bang Cong Vu

The exact complexity of geometric cuts and bisections is the longstanding open problem including even the dimension one. In this paper, we resolve this problem for dimension one (the real line) by designing an exact polynomial time…

Data Structures and Algorithms · Computer Science 2012-07-05 Marek Karpinski , Andrzej Lingas , Dzmitry Sledneu

The aim of the paper is to propose a bounded-error quantum polynomial time (BQP) algorithm for the max-bisection and the min-bisection problems. The max-bisection and the min-bisection problems are fundamental NP-hard problems. Given a…

Quantum Physics · Physics 2015-07-27 Ahmed Younes

Dual descent methods are commonly used to solve network optimization problems because their implementation can be distributed through the network. However, their convergence rates are typically very slow. This paper introduces a family of…

Optimization and Control · Mathematics 2011-04-07 M. Zargham , A. Ribeiro , A. Jadbabaie , A. Ozdaglar

The optimization of expensive-to-evaluate black-box functions over combinatorial structures is an ubiquitous task in machine learning, engineering and the natural sciences. The combinatorial explosion of the search space and costly…

Machine Learning · Statistics 2018-10-11 Ricardo Baptista , Matthias Poloczek

For optimization problems on Riemannian manifolds, many types of globally convergent algorithms have been proposed, and they are often equipped with the Riemannian version of the Armijo line search for global convergence. Such existing…

Optimization and Control · Mathematics 2025-04-11 Hiroyuki Sato , Yuya Yamakawa , Kensuke Aihara

In this paper we analyze O'Hara's partition bijection. We present three type of results. First, we show that O'Hara's bijection can be viewed geometrically as a certain scissor congruence type result. Second, we obtain a number of new…

Combinatorics · Mathematics 2007-10-09 Matjaz Konvalinka , Igor Pak

In this paper, a tunneling method is developed for nonlinear multiobjective optimization problems using some ideas of the single objective tunneling method. The proposed method does not require any a priori chosen parameters or ordering…

Optimization and Control · Mathematics 2025-10-06 Bikram Adhikary , Md Abu Talhamainuddin Ansary

We show that an algorithmic construction of sequences of recursive trees leads to a direct proof of the convergence of random recursive trees in an associated Doob-Martin compactification; it also gives a representation of the limit in…

Probability · Mathematics 2014-07-01 Rudolf Grübel , Igor Michailow

We develop a new Riemannian descent algorithm that relies on momentum to improve over existing first-order methods for geodesically convex optimization. In contrast, accelerated convergence rates proved in prior work have only been shown to…

Optimization and Control · Mathematics 2021-02-16 Foivos Alimisis , Antonio Orvieto , Gary Bécigneul , Aurelien Lucchi

Dual descent methods are commonly used to solve network flow optimization problems, since their implementation can be distributed over the network. These algorithms, however, often exhibit slow convergence rates. Approximate Newton methods…

Optimization and Control · Mathematics 2015-03-25 Rasul Tutunov , Haitham Bou Ammar , Ali Jadbabaie

Approximate Bayesian Computation (ABC) methods are increasingly used for inference in situations in which the likelihood function is either computationally costly or intractable to evaluate. Extensions of the basic ABC rejection algorithm…

Computation · Statistics 2020-05-01 Umberto Simola , Jessica Cisewski-Kehe , Michael U. Gutmann , Jukka Corander

In this paper, we present an algorithm which allows us to search for all the bisections for the binomial coefficients $\{\binom{n}{k} \}_{k=0,...,n}$ and include a table with the results for all $n\le 154$. Connections with previous work on…

Combinatorics · Mathematics 2018-03-28 Eugen J. Ionascu

We revisit the classical dual ascent algorithm for minimization of convex functionals in the presence of linear constraints, and give convergence results which apply even for non-convex functionals. We describe limit points in terms of the…

Optimization and Control · Mathematics 2016-09-22 Fredrik Andersson , Marcus Carlsson , Carl Olsson

This article develops a new predictor-corrector algorithm for numerical path tracking in the context of polynomial homotopy continuation. In the corrector step it uses a newly developed Newton corrector algorithm which rejects an initial…

Numerical Analysis · Mathematics 2020-03-24 Sascha Timme

A new network construction method is presented for building of scalable, high throughput, low latency networks. The method is based on the exact equivalence discovered between the problem of maximizing network throughput (measured as…

Information Theory · Computer Science 2013-02-06 Ratko V. Tomic

Recent advancements in quantum computing and quantum-inspired algorithms have sparked renewed interest in binary optimization. These hardware and software innovations promise to revolutionize solution times for complex problems. In this…

We discuss the application of the Mountain Pass algorithm to the so-called quasi-linear Schrodinger equation, which is naturally associated with a class of nonsmooth functionals so that the classical algorithm is not directly applicable.

Numerical Analysis · Mathematics 2012-11-13 Christopher Grumiau , Marco Squassina , Christophe Troestler