Acyclic Graphs
A Recursive Method for Structural Learning of Directed Acyclic Graphs
... directed acyclic graphs (DAGs), in which a problem of structural learning for a large DAG is first decomposed into two problems of structural learning for two small vertex subsets, each of which is then ...
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A Novel Path Enumeration Algorithm for Directed Acyclic Graphs
... directed acyclic graphs using a simple C++ method reported by [9], interested readers or researchers may as well try to compare the performance of our methods with DFS based path enumeration, for the ...
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A Novel Approach for Resilient Multipath Routing by Using Independent Directed Acyclic Graphs
... In this paper, we introduce the concept of Independent Directed Acyclic Graphs (IDAGs) to achieve resilient multipath routing. The algorithm developed in this paper: (1) achieves multipath routing; (2) ...
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Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs
... directed acyclic graphs (DAGs) encoding the same Markov property, that is the same conditional independence relations of multivariate observational distributions, has a long tradition; many algorithms exist ...
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Fixed parameter tractability of multicut in directed acyclic graphs
... undirected graphs, parameterized by the size of the cutset only, has been recently proved by Marx and Razgon [SIAM ...directed acyclic graphs when parameterized both by the size of the cutset and the ...
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Properties of Monotonic Effects on Directed Acyclic Graphs
... the notation we will use in this paper and review the definitions concerning directed acyclic graphs. In Section 3 we present a motivating example for the theory that will be developed. In Section 4, we ...
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Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm
... directed acyclic graphs (DAGs), containing directed rather than undirected edges, which restrict in a sense the conditional dependence ...These graphs can be interpreted by applying the directed ...
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Counting and Sampling Markov Equivalent Directed Acyclic Graphs
... directed acyclic graphs (DAGs) in a Markov equiv- alence class is pivotal to infer causal effects or to dis- cover the causal DAG via appropriate interventional ...moral acyclic orientations of a ...
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Multipath Routing With Directed Acyclic Graphs in MANETS
... directed acyclic graphs is presented in this paper and developed polynomial time algorithms to construct node independent and link independent DAGs using all possible edges in the ...
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DAGGER: A Toolkit for Automata on Directed Acyclic Graphs
... Finite string automata and finite tree automata have proved to be useful tools in various areas of natural language processing (Knight and May, 2009). How- ever, some applications, especially in semantics, re- quire ...
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Using directed acyclic graphs in epidemiological research in psychosis : an analysis of the role of bullying in psychosis
... Modern psychiatric epidemiology researches complex inter- actions between multiple variables in large datasets. This creates difficulties for causal inference. We argue for the use of probabilistic models represented by ...
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Counting and Exploring Sizes of Markov Equivalence Classes of Directed Acyclic Graphs
... The complexity of calculating SizeMEC(U ) via Algorithm 2 depends on the number of times this recursive function is called. Our experiments in the next section show that when the number of vertices in U is small, or when ...
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Combining directed acyclic graphs and the change-in-estimate procedure as a novel approach to adjustment-variable selection in epidemiology
... Such bias amplification can also lead to a change in the effect estimate when adjusting on different variable sets, so researchers should consider it when reviewing a DAG Figure 3 Direct[r] ...
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Reducing bias through directed acyclic graphs
... One method to help understand whether bias is poten- tially reduced or increased when conditioning on covari- ates is the graphical representation of causal effects between variables. In the causal directed ...
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An O(βn) Approximation and Integrality Gap for Disjoint Paths and Unsplittable Flow
... directed acyclic graphs ...directed graphs is hard to approximate within a factor of O(m 1/2βΞ΅ ) unless P = ...sparse graphs, and hence as a function of n, it establishes a hardness factor of ...
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FLEXIBLE SHARING IN DHT BASED P2P NETWORKS USING METADATA OF RESOURCE
... undirected acyclic graphs, which contain two steps: eliminating the direction of the diffusion trees and adding some edges which exist in the social network and also whose nodes are affected in the spread ...
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Complete Graphical Characterization and Construction of Adjustment Sets in Markov Equivalence Classes of Ancestral Graphs
... chain graphs (representing a subset of a Markov equivalence class of ...directed acyclic graphs (PDAGs), which represent CPDAGs with added background ...
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Vol 7, No 4 (2016)
... We know that among all acyclic graphs, the star πΎπΎ 1,( π‘π‘β 1) has a minimum Wiener index and path graph ππ ππ has a maximum Wiener index.. So, we can get extreme class of graphs in[r] ...
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The Reduced PC-Algorithm: Improved Causal Structure Learning in Large Random Networks
... directed acyclic graph is the undirected graph obtained by removing the direction of ...directed acyclic graph (CPDAG) represents the class of all directed acyclic graphs that are Markov ...
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A Review on Human Gender Classification Based on Face Feature Extraction
... As Zholiu points out, over 33% of the digital data can prove valuable if we have proper tools and methods to analyse it whereas the current uses scores up to mere 0.5%. These kinds of observations initiate the need of ...
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