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Historically, scalability has been a major challenge to the successful application of semidefinite programming in fields such as machine learning, control, and robotics. In this paper, we survey recent approaches for addressing this…

Optimization and Control · Mathematics 2019-12-18 Anirudha Majumdar , Georgina Hall , Amir Ali Ahmadi

Component substitution has numerous practical applications and constitutes an active research topic. This paper proposes to enrich an existing component-based framework--a model with dynamic reconfigurations making the system evolve--with a…

Software Engineering · Computer Science 2014-08-10 Arnaud Lanoix , Olga Kouchnarenko

We introduce a notion of compatibility between constraint encoding and compositional structure. Phrased in the language of category theory, it is given by a "composable constraint encoding". We show that every composable constraint encoding…

Category Theory · Mathematics 2021-12-14 Matt Wilson , Augustin Vanrietvelde

Literature on Constraint Satisfaction exhibits the definition of several structural properties that can be possessed by CSPs, like (in)consistency, substitutability or interchangeability. Current tools for constraint solving typically…

Artificial Intelligence · Computer Science 2014-01-16 Lucas Bordeaux , Marco Cadoli , Toni Mancini

In the last years many results in the area of semidefinite programming were obtained for invariant (finite dimensional, or infinite dimensional) semidefinite programs - SDPs which have symmetry. This was done for a variety of problems and…

Optimization and Control · Mathematics 2019-11-07 Christine Bachoc , Dion C. Gijswijt , Alexander Schrijver , Frank Vallentin

Constraint programming is used for a variety of real-world optimisation problems, such as planning, scheduling and resource allocation problems. At the same time, one continuously gathers vast amounts of data about these problems. Current…

Constraint answer set programming is a promising research direction that integrates answer set programming with constraint processing. It is often informally related to the field of satisfiability modulo theories. Yet, the exact formal link…

Logic in Computer Science · Computer Science 2017-02-27 Yuliya Lierler , Benjamin Susman

The area of research called \textquotedblleft Lineability\textquotedblright% \ looks for linear structures inside exotic subsets of vector spaces. In the last decade lineability/spaceability has been investigated in rather general settings;…

Functional Analysis · Mathematics 2018-09-10 Vinícius Fávaro , Daniel Pellegrino , Daniel Tomaz

We review old and new uses of exchangeability, emphasizing the general theme of exchangeable representations of complex random structures. Illustrations of this theme include processes of stochastic coalescence and fragmentation; continuum…

Probability · Mathematics 2010-02-22 David J. Aldous

One approach to confronting computational hardness is to try to understand the contribution of various parameters to the running time of algorithms and the complexity of computational tasks. Almost no computational tasks in real life are…

Computational Complexity · Computer Science 2011-11-23 Rodney G. Downey , Dimitrios M. Thilikos

Symmetry is an important feature of many constraint programs. We show that any problem symmetry acting on a set of symmetry breaking constraints can be used to break symmetry. Different symmetries pick out different solutions in each…

Artificial Intelligence · Computer Science 2010-05-31 George Katsirelos , Toby Walsh

New measures for the quantization of systems with constraints are discussed and applied to several examples, in particular, examples of alternative but equivalent formulations of given first-class constraints, as well as a comparison of…

Quantum Physics · Physics 2007-05-23 John R. Klauder

The min-knapsack problem with compactness constraints extends the classical knapsack problem, in the case of ordered items, by introducing a restriction ensuring that they cannot be too far apart. This problem has applications in…

Optimization and Control · Mathematics 2025-04-28 Hubert Villuendas , Mathieu Besançon , Jérôme Malick

Intuitively, if we can prove that a program terminates, we expect some conclusion regarding its complexity. But the passage from termination proofs to complexity bounds is not always clear. In this work we consider Monotonicity Constraint…

Logic in Computer Science · Computer Science 2014-05-01 Amir M. Ben-Amram , Michael Vainer

Twenty years ago, in an article titled "Covariance and contravariance: conflict without a cause", I argued that covariant and contravariant specialization of method parameters in object-oriented programming had different purposes and…

Programming Languages · Computer Science 2023-06-22 Giuseppe Castagna

Symmetry is a common feature of many combinatorial problems. Unfortunately eliminating all symmetry from a problem is often computationally intractable. This paper argues that recent parameterized complexity results provide insight into…

Artificial Intelligence · Computer Science 2015-05-19 Toby Walsh

In this paper, we investigate the structure of the most general kind of substitution shifts, including non-minimal ones, and allowing erasing morphisms. We prove the decidability of many properties of these morphisms with respect to the…

Dynamical Systems · Mathematics 2024-04-03 Marie-Pierre Béal , Dominique Perrin , Antonio Restivo

Distributed computation in artificial life and complex systems is often described in terms of component operations on information: information storage, transfer and modification. Information modification remains poorly described however,…

Information Theory · Computer Science 2013-10-10 Joseph T. Lizier , Benjamin Flecker , Paul L. Williams

We recall some of the early occurrences of the notions of interactivity and symmetry in the operational and denotational semantics of programming languages. We suggest some connections with ludics.

Logic in Computer Science · Computer Science 2007-06-17 Pierre-Louis Curien

To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision variables (which we can set) and stochastic variables…

Artificial Intelligence · Computer Science 2009-03-09 Toby Walsh
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