Sep 8, 2022 · (The LOCAL model) We consider an arbitrary n-node graph G= (V , E) where V= f1 , 2 , ::: ng , which abstracts the communication network. Unless noted otherwise, G is a …

• A deterministic algorithm is the one that produces the same output for a problem instance each time the algorithm is run. • A non-deterministic algorithm is a two-stage procedure that takes …

Now that we have introduced the essential graph-theoretic concepts, we are ready to define what a “distributed algorithm” is. In this chapter, we will study one variant of the theme: deterministic …

• Introduction: Constraint and probabilistic graphical models. • Constraint networks: Graphs, modeling, Inference • Inference in constraints: Adaptive consistency, constraint propagation, …

We surveyed quite a wide array of literature in algorithms, mathematical programming and spectral graph theory. Major contribution is empirical evidence of various approximation …

• How do we score any particular model (i.e., graph) given data? • How do we find a model with the highest score? We present the frequentist perspective first before looking at the Bayesian …

Nov 11, 2015 · The main feature exploited by the algorithms is the model's graph. We present inference-based, message-passing schemes (e.g., variable-elimination) and search-based, …

Particularly, we propose a deterministic algo-rithm that computes a maximal independent set in time O(log ¢¢log¤n) in graphs with bounded growth, where n and ¢ denote the number of …

We develop a conceptually simple modeling technique called deterministic task graph analysis that provides detailed performance prediction for shared-memory programs with arbitrary task …

Oct 1, 2019 · We present O (1)-time deterministic algorithms (hence, optimal) for computing MIS in unit interval graphs, unit square graphs and unit disk graphs. The same idea applies to …