17 papers · ranked by Valyu relevance
Frédéric Herbreteau, Sarah Larroze-Jardiné, Gérald Point, Igor Walukiewicz
'Igor Walukiewicz'] The goal of partial-order methods is to accelerate the exploration of concurrent systems by examining only a representative subset of all possible runs. The stateful approach builds a transition system with representative runs, while the stateless method simply enumerates them. The stateless…
Chuchu Fan, Zhenqi Huang, Sayan Mitra
We present a new partial order reduction method for reachability analysis of nondeterministic labeled transition systems over metric spaces. Nondeterminism arises from both the choice of the initial state and the choice of actions, and the number of executions to be explored grows exponentially with their length. We…
Patrick Bahr
> Abstract. We study an alternative model of infinitary term rewriting. Instead of a metric on terms, a partial order on partial terms is employed to formalise convergence of reductions. We consider both a weak and a strong notion of convergence and show that the metric model of convergence coincides with the partial…
Shuvendu K. Lahiri, Chao Wang, Daniel Schemmel, Julian Büning + 3 more
'César Rodríguez' 'David Laprell' 'Klaus Wehrle'] We describe a technique for systematic testing of multi-threaded programs. We combine Quasi-Optimal Partial-Order Reduction, a state-of-the-art technique that tackles path explosion due to interleaving non-determinism, with symbolic execution to handle data…
Liyong Lin, Tomáš Masopust, W.M. Wonham, Rong Su
—A reduction of a source distribution is a collection of smaller sized distributions that are collectively equivalent to the source distribution with respect to the property of decomposability. That is, an arbitrary language is decomposable with respect to the source distribution if and only if it is decomposable with…
Sławomir Solecki
This is a survey of recent work on the structure of Tukey reductions among analytic σ-ideals of compact subsets of compact metric spaces and analytic P-ideals of sets of natural numbers. An attempt is made to organize the results into a unified whole. This organization makes it possible to identify natural unresolved…
Alexander V. Gheorghiu, David J. Pym
The development of logic has largely been through the deductive paradigm: conclusions are inferred from established premisses. However, the use of logic in the context of both human and machine reasoning is typically through the dual reductive perspective: collections of sufficient premisses are generated from putative…
Jan Maly, Stefan Woltran
Ranking sets of objects based on an order between the single elements has been thoroughly studied in the literature. In particular, it has been shown that it is in general impossible to find a total ranking - jointly satisfying properties as dominance and independence - on the whole power set of objects. However, in…
Caitlin Lienkaemper, Lisa Lamberti, James Drain, Niko Beerenwinkel + 1 more
We present an efficient computational approach for detecting genetic interactions from fitness comparison data together with a geometric interpretation using polyhedral cones associated to partial orderings. Genetic interactions are defined by linear forms with integer coefficients in the fitness variables assigned to…
Andrew A. Chen, Kelly Clark, Blake Dewey, Anna DuVal + 10 more
Dimension reduction tools preserving similarity and graph structure such as t-SNE and UMAP can capture complex biological patterns in high-dimensional data. However, these tools typically are not designed to separate effects of interest from unwanted effects due to confounders. We introduce the partial embedding (PARE)…
Ayush Pandey, Richard M. Murray
We present an automated model reduction algorithm that uses quasi-steady state approximation based reduction to minimize the error between the desired outputs. Additionally, the algorithm minimizes the sensitivity of the error with respect to parameters to ensure robust performance of the reduced model in the presence…
Zhuo Chen, Hongyu Yang, Yanli Liu, Lei Wang
The order reduction method is an important approach to optimize higher-order binary Markov random fields (HoMRFs), which are widely used in information theory, machine learning and image analysis. It transforms an HoMRF into an equivalent and easier reduced first-order binary Markov random field (RMRF) by elaborately…
Ayush Pandey, Richard M. Murray
We present a Python-based software package to automatically obtain phenomenological models of input-controlled synthetic biological circuits that guide the design using chemical reaction-level descriptive models. From the parts and mechanism description of a synthetic biological circuit, it is easy to obtain a chemical…
Alberto Padoan, Fulvio Forni, Rodolphe Sepulchre
Model reduction is a central problem in mathematical biology. Reduced order models enable modeling of a biological system at different levels of complexity and the quantitative analysis of its properties, like sensitivity to parameter variations and resilience to exogenous perturbations. However, available model…
Mojtaba Tefagh, Stephen Boyd
Genome-scale metabolic networks are exceptionally huge and even efficient algorithms can take a while to run because of the sheer size of the problem instances. To address this problem, metabolic network reductions can substantially reduce the overwhelming size of the problem instances at hand. We begin by formulating…
Wen Chen
In a recent paper by the author (Chen in JHEP 02:115, 2020), the reduction of Feynman integrals in the parametric representation was considered. Tensor integrals were directly parametrized by using a generator method. The resulting parametric integrals were reduced by constructing and solving parametric…
Yoshio Nishimoto
Analytic gradients for the partially renormalized second-order Moller-Plesset perturbation theory (Scheme I) are derived using the Lagrangian method. This is just a technical document and is not intended for publication.