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Lipton's reduction theory provides an intuitive and simple way for deducing the non-interference properties of concurrent programs, but it is difficult to directly apply the technique to verify linearizability of sophisticated fine-grained…

Programming Languages · Computer Science 2018-08-31 Tangliu Wen

Multi-modal multi-objective optimization aims to find all Pareto optimal solutions including overlapping solutions in the objective space. Multi-modal multi-objective optimization has been investigated in the evolutionary computation…

Neural and Evolutionary Computing · Computer Science 2020-09-29 Ryoji Tanabe , Hisao Ishibuchi

Collective communications are ubiquitous in parallel applications. We present two new algorithms for performing a reduction. The operation associated with our reduction needs to be associative and commutative. The two algorithms are…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-10-18 Bradley R. Lowery , Julien Langou

Optimization has found numerous applications in engineering, particularly since 1960s. Many optimization applications in engineering have more than one objective (or performance criterion). Such applications require multi-objective (or…

Chemical Physics · Physics 2024-07-16 Zhiyuan Wang , Seyed Reza Nabavi , Gade Pandu Rangaiah

Online-learning research has mainly been focusing on minimizing one objective function. In many real-world applications, however, several objective functions have to be considered simultaneously. Recently, an algorithm for dealing with…

Machine Learning · Computer Science 2017-03-21 Guy Uziel , Ran El-Yaniv

Distributed proofs are mechanisms enabling the nodes of a network to collectivity and efficiently check the correctness of Boolean predicates on the structure of the network, or on data-structures distributed over the nodes (e.g., spanning…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-09-22 Laurent Feuilloley , Pierre Fraigniaud , Juho Hirvonen , Ami Paz , Mor Perry

In this paper, we deal with two ingredients that, as far as we know, have not been combined until now: multiobjective optimization and discrete convex analysis. First, we show that the entire Pareto optimal value set can be obtained in…

Optimization and Control · Mathematics 2026-02-20 Ellen H. Fukuda , Satoru Iwata , Itsuki Nakagawa

First-order optimization methods have attracted a lot of attention due to their practical success in many applications, including in machine learning. Obtaining convergence guarantees and worst-case performance certificates for first-order…

Optimization and Control · Mathematics 2023-10-04 Baptiste Goujaud , Aymeric Dieuleveut , Adrien Taylor

Real-world contracts are often ambiguous. While recent work by D\"utting, Feldman, Peretz, and Samuelson (EC 2023, Econometrica 2024) demonstrates that ambiguous contracts can yield large gains for the principal, their optimal solutions…

Computer Science and Game Theory · Computer Science 2026-02-27 Paul Duetting , Michal Feldman , Yarden Rashti

A key task in multi-objective optimization is to compute the Pareto subset or frontier $P$ of a given $d$-dimensional objective space $F$; that is, a maximal subset $P\subseteq F$ such that every element in $P$ is not-dominated (it is not…

Data Structures and Algorithms · Computer Science 2025-08-29 Konstantinos Karathanasis , Spyros Kontogiannis , Christos Zaroliagis

In this paper, a descent method for nonsmooth multiobjective optimization problems on complete Riemannian manifolds is proposed. The objective functions are only assumed to be locally Lipschitz continuous instead of convexity used in…

Optimization and Control · Mathematics 2025-01-14 Chunming Tang , Hao He , Jinbao Jian , Miantao Chao

Most real-world Planning problems are multi-objective, trying to minimize both the makespan of the solution plan, and some cost of the actions involved in the plan. But most, if not all existing approaches are based on single-objective…

Artificial Intelligence · Computer Science 2013-05-07 Mostepha Redouane Khouadjia , Marc Schoenauer , Vincent Vidal , Johann Dréo , Pierre Savéant

This paper is devoted to general nonconvex problems of multiobjective optimization in Hilbert spaces. Based on Mordukhovich's limiting subgradients, we define a new notion of Pareto critical points for such problems, establish necessary…

Optimization and Control · Mathematics 2024-03-18 G. C. Bento , J. X. Cruz Neto , J. O. Lopes , B. S. Mordukhovich , P. R. Silva Filho

We study a class of convex-concave min-max problems in which the coupled component of the objective is linear in at least one of the two decision vectors. We identify such problem structure as interpolating between the bilinearly and…

Optimization and Control · Mathematics 2025-07-10 Ronak Mehta , Jelena Diakonikolas , Zaid Harchaoui

With the advent of multi-core processors, network-on-chip design has been key in addressing network performances, such as bandwidth, power consumption, and communication delays when dealing with on-chip communication between the increasing…

Emerging Technologies · Computer Science 2018-08-01 Tzyy-Juin Kao , Wolfgang Fink

While globally optimal solutions to many convex programs can be computed efficiently in polynomial time, this is, in general, not possible for nonconvex optimization problems. Therefore, locally optimal approaches or other efficient…

Information Theory · Computer Science 2020-07-03 Bho Matthiesen , Christoph Hellings , Eduard A. Jorswieck , Wolfgang Utschick

We will investigate proof-theoretic and linguistic aspects of first-order linear logic. We will show that adding partial order constraints in such a way that each sequent defines a unique linear order on the antecedent formulas of a sequent…

Logic in Computer Science · Computer Science 2020-08-17 Richard Moot

The aim of this short note is twofold. First, we give a sketch of the proof of a recent result proved by the authors in the paper [Colombo, Crippa, and Spirito, Calc. Var. Partial Differential Equations 2015] concerning existence and…

Analysis of PDEs · Mathematics 2018-11-07 Maria Colombo , Gianluca Crippa , Stefano Spirito

Team assembly is a problem that demands trade-offs between multiple fairness criteria and computational optimization. We focus on four criteria: (i) fair distribution of workloads within the team, (ii) fair distribution of skills and…

Databases · Computer Science 2023-06-27 Rodrigo Borges , Otto Sahlgrens , Sami Koivunen , Kostas Stefanidis , Thomas Olsson , Arto Laitinen

We settle the computational complexity of fundamental questions related to multicriteria integer linear programs, when the dimensions of the strategy space and of the outcome space are considered fixed constants. In particular we construct:…

Optimization and Control · Mathematics 2017-01-03 Jesús A. De Loera , Raymond Hemmecke , Matthias Köppe
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