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Littérature scientifique sur le sujet « Differential Graph »

Auteur : Grafiati

Publié le 9 mars 2023

Mis à jour le 10 mars 2023

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Articles de revues sur le sujet "Differential Graph"

Chen, Yuanmei, Haizhen Ren, Lei Zhang et Yang Zhao. « Computation of Differential in Strong Product Network of Paths via Recursive Iteration ». Journal of Physics : Conference Series 2025, n^o 1 (1 septembre 2021) : 012050. http://dx.doi.org/10.1088/1742-6596/2025/1/012050.

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Abstract The set differential can be attributed to some influence maximization problems, which are widely used. For example, it is a basic algorithm problem of information diffusion in social networks. In 2004, Lewis et al. extended this concept to the graph, defined the differential of graph. The present article mainly studies the differential in strong product network of paths. Using the basic block recursive iterative method, we obtain closed form formulas for the differential on the strong product network of paths. The method used here is also effective for the differentials in square graphs.

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B, Vembu, et Loghambal S. « Pseudo-Graph Neural Networks On Ordinary Differential Equations ». Journal of Computational Mathematica 6, n^o 1 (22 mars 2022) : 117–23. http://dx.doi.org/10.26524/cm.125.

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In this paper, we extend the idea of continuous-depth models to pseudo graphs and present pseudo graph ordinary differential equations (PGODE), which are inspired by the neural ordinary differential equation (NODE) for data in the Euclidean domain. All existing graph networks have discrete depth. A pseudo graph neural network (PGNN) is used to parameterize the derivative of hidden node states, and the output states are the solution to this ordinary differential equation (ODE). A memory-efficient framework with precise gradient estimates is then proposed for free-form ODEs. We also introduce the framework of continuous–depth pseudo graph neural networks (PGNNs) on ODE by blending discrete structures and differential equations

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Chen, Xihui, Sjouke Mauw et Yunior Ramírez-Cruz. « Publishing Community-Preserving Attributed Social Graphs with a Differential Privacy Guarantee ». Proceedings on Privacy Enhancing Technologies 2020, n^o 4 (1 octobre 2020) : 131–52. http://dx.doi.org/10.2478/popets-2020-0066.

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AbstractWe present a novel method for publishing differentially private synthetic attributed graphs. Our method allows, for the first time, to publish synthetic graphs simultaneously preserving structural properties, user attributes and the community structure of the original graph. Our proposal relies on CAGM, a new community-preserving generative model for attributed graphs. We equip CAGM with efficient methods for attributed graph sampling and parameter estimation. For the latter, we introduce differentially private computation methods, which allow us to release communitypreserving synthetic attributed social graphs with a strong formal privacy guarantee. Through comprehensive experiments, we show that our new model outperforms its most relevant counterparts in synthesising differentially private attributed social graphs that preserve the community structure of the original graph, as well as degree sequences and clustering coefficients.

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Pushpam, P. Roushini Leely, et D. Yokesh. « Differentials in certain classes of graphs ». Tamkang Journal of Mathematics 41, n^o 2 (30 juin 2010) : 129–38. http://dx.doi.org/10.5556/j.tkjm.41.2010.664.

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Let $X subset V$ be a set of vertices in a graph $G = (V, E)$. The boundary $B(X)$ of $X$ is defined to be the set of vertices in $V-X$ dominated by vertices in $X$, that is, $B(X) = (V-X) cap N(X)$. The differential $ partial(X)$ of $X$ equals the value $ partial(X) = |B(X)| - |X|$. The differential of a graph $G$ is defined as $ partial(G) = max { partial(X) | X subset V }$. It is easy to see that for any graph $G$ having vertices of maximum degree $ Delta(G)$, $ partial(G) geq Delta (G) -1$. In this paper we characterize the classes of unicyclic graphs, split graphs, grid graphs, $k$-regular graphs, for $k leq 4$, and bipartite graphs for which $ partial(G) = Delta(G)-1$. We also determine the value of $ partial(T)$ for any complete binary tree $T$.

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Konyrkulzhayeva, М. N. « THE DIRICHLET PROBLEM ON THE ORIENTED GRAPHS ». BULLETIN Series of Physics & ; Mathematical Sciences 70, n^o 2 (30 juin 2020) : 84–90. http://dx.doi.org/10.51889/2020-2.1728-7901.12.

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Differential operators on graphs often arise in mathematics and different fields of science such as mechanics, physics, organic chemistry, nanotechnology, etc. In this paper the solutions of the Dirichlet problem for a differential operator on a star-shaped graph are deduced. And the differential operator with standard matching conditions in the internal vertices and the Dirichlet boundary conditions at boundary vertices are studied. Task is a model the oscillation of a simple system of several rods with an adjacent end. In work the formula of the Green function of the Dirichlet problem for the second order equation on directed graph is showed. Spectral analysis of differential operators on geometric graphs is the basic mathematical apparatus in solving modern problems of quantum mechanics.

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Basilio, Ludwin, Sergio Bermudo, Jesús Leaños et José Sigarreta. « β-Differential of a Graph ». Symmetry 9, n^o 10 (30 septembre 2017) : 205. http://dx.doi.org/10.3390/sym9100205.

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Wang, Weiya, Geng Yang, Lin Bao, Ke Ma, Hao Zhou et Yunlu Bai. « Travel Trajectory Frequent Pattern Mining Based on Differential Privacy Protection ». Wireless Communications and Mobile Computing 2021 (5 août 2021) : 1–14. http://dx.doi.org/10.1155/2021/6379530.

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Now, many application services based on location data have brought a lot of convenience to people’s daily life. However, publishing location data may divulge individual sensitive information. Because the location records about location data may be discrete in the database, some existing privacy protection schemes are difficult to protect location data in data mining. In this paper, we propose a travel trajectory data record privacy protection scheme (TMDP) based on differential privacy mechanism, which employs the structure of a trajectory graph model on location database and frequent subgraph mining based on weighted graph. Time series is introduced into the location data; the weighted trajectory model is designed to obtain the travel trajectory graph database. We upgrade the mining of location data to the mining of frequent trajectory graphs, which can discover the relationship of location data from the database and protect location data mined. In particular, to improve the identification efficiency of frequent trajectory graphs, we design a weighted trajectory graph support calculation algorithm based on canonical code and subgraph structure. Moreover, to improve the data utility under the premise of protecting user privacy, we propose double processes of adding noises to the subgraph mining process by the Laplace mechanism and selecting final data by the exponential mechanism. Through formal privacy analysis, we prove that our TMDP framework satisfies ε -differential privacy. Compared with the other schemes, the experiments show that the data availability of the proposed scheme is higher and the privacy protection of the scheme is effective.

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Rezapour, Shahram, Chernet Tuge Deressa, Azhar Hussain, Sina Etemad, Reny George et Bashir Ahmad. « A Theoretical Analysis of a Fractional Multi-Dimensional System of Boundary Value Problems on the Methylpropane Graph via Fixed Point Technique ». Mathematics 10, n^o 4 (12 février 2022) : 568. http://dx.doi.org/10.3390/math10040568.

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Few studies have investigated the existence and uniqueness of solutions for fractional differential equations on star graphs until now. The published papers on the topic are based on the assumption of existence of one junction node and some boundary nodes as the origin on a star graph. These structures are special cases and do not cover more general non-star graph structures. In this paper, we state a labeling method for graph vertices, and then we prove the existence results for solutions to a new family of fractional boundary value problems (FBVPs) on the methylpropane graph. We design the chemical compound of the methylpropane graph with vertices specified by 0 or 1, and on every edge of the graph, we consider fractional differential equations. We prove the existence of solutions for the proposed FBVPs by means of the Krasnoselskii’s and Scheafer’s fixed point theorems, and further, we study the Ulam–Hyers type stability for the given multi-dimensional system. Finally, we provide an illustrative example to examine our results.

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Basilio, Ludwin A., Sergio Bermudo, Juan C. Hernández-Gómez et José M. Sigarreta. « General Properties on Differential Sets of a Graph ». Axioms 10, n^o 4 (20 octobre 2021) : 265. http://dx.doi.org/10.3390/axioms10040265.

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Let G=(V,E) be a graph, and let β∈R. Motivated by a service coverage maximization problem with limited resources, we study the β-differential of G. The β-differential of G, denoted by ∂β(G), is defined as ∂β(G):=max{|B(S)|−β|S|suchthatS⊆V}. The case in which β=1 is known as the differential of G, and hence ∂β(G) can be considered as a generalization of the differential ∂(G) of G. In this paper, upper and lower bounds for ∂β(G) are given in terms of its order |G|, minimum degree δ(G), maximum degree Δ(G), among other invariants of G. Likewise, the β-differential for graphs with heavy vertices is studied, extending the set of applications that this concept can have.

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Remiddi, E. « Differential equations for Feynman graph amplitudes ». Il Nuovo Cimento A 110, n^o 12 (décembre 1997) : 1435–52. http://dx.doi.org/10.1007/bf03185566.

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Thèses sur le sujet "Differential Graph"

Vasilyeva, Elena, Maik Thiele, Christof Bornhövd et Wolfgang Lehner. « Considering User Intention in Differential Graph Queries ». IGI Global, 2015. https://tud.qucosa.de/id/qucosa%3A72931.

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Empty answers are a major problem by processing pattern matching queries in graph databases. Especially, there can be multiple reasons why a query failed. To support users in such situations, differential queries can be used that deliver missing parts of a graph query. Multiple heuristics are proposed for differential queries, which reduce the search space. Although they are successful in increasing the performance, they can discard query subgraphs relevant to a user. To address this issue, the authors extend the concept of differential queries and introduce top-k differential queries that calculate the ranking based on users’ preferences and significantly support the users’ understanding of query database management systems. A user assigns relevance weights to elements of a graph query that steer the search and are used for the ranking. In this paper the authors propose different strategies for selection of relevance weights and their propagation. As a result, the search is modelled along the most relevant paths. The authors evaluate their solution and both strategies on the DBpedia data graph.

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ARTARIA, ANDREA. « Objective Bayesian Analysis for Differential Gaussian Directed Acyclic Graphs ». Doctoral thesis, Università degli Studi di Milano-Bicocca, 2014. http://hdl.handle.net/10281/55327.

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Often we are confronted with heterogeneous multivariate data, i.e., data coming from several categories, and the interest may center on the differential structure of stochastic dependence among the variables between the groups. The focus in this work is on the two groups problem and is faced modeling the system through a Gaussian directed acyclic graph (DAG) couple linked in a fashion to obtain a joint estimation in order to exploit, whenever they exist, similarities between the graphs. The model can be viewed as a set of separate regressions and the proposal consists in assigning a non-local prior to the regression coefficients with the objective of enforcing stronger sparsity constraints on model selection. The model selection is based on Moment Fractional Bayes Factor, and is performed through a stochastic search algorithm over the space of DAG models.

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Lewis, Jason Robert. « Differentials of graphs ». [Johnson City, Tenn. : East Tennessee State University], 2004. http://etd-submit.etsu.edu/etd/theses/available/etd-0322104-155516/unrestricted/LewisJason040604f.pdf.

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Thesis (M.S.)--East Tennessee State University, 2004.
Title from electronic submission form. ETSU ETD database URN: etd-0322104-155516. Includes bibliographical references. Also available via Internet at the UMI web site.

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Christensen, Robin. « An Analysis of Notions of Differential Privacy for Edge-Labeled Graphs ». Thesis, Linköpings universitet, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-169379.

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The user data in social media platforms is an excellent source of information that is beneficial for both commercial and scientific purposes. However, recent times has seen that the user data is not always used for good, which has led to higher demands on user privacy. With accurate statistical research data being just as important as the privacy of the user data, the relevance of differential privacy has increased. Differential privacy allows user data to be accessible under certain privacy conditions at the cost of accuracy in query results, which is caused by noise. The noise is based on a tuneable constant ε and the global sensitivity of a query. The query sensitivity is defined as the greatest possible difference in query result between the queried database and a neighboring database. Where the neighboring database is defined to differ by one record in a tabular database, there are multiple neighborhood notions for edge-labeled graphs. This thesis considers the notions of edge neighborhood, node neighborhood, QL-edge neighborhood and QL-outedges neighborhood. To study these notions, a framework was developed in Java to function as a query mechanism for a graph database. ArangoDB was used as a storage for graphs, which was generated by parsing data sets in the RDF format as well as through a graph synthesizer in the developed framework. Querying a database in the framework is done with Apache TinkerPop, and a Laplace distribution is used when generating noise for the query results. The framework was used to study the privacy and utility trade-off of different histogram queries on a number of data sets, while employing the different notions of neighborhood in edge-labeled graphs. The level of privacy is determined by the value on ε, and the utility is defined as a measurement based on the L1-distance between the true and noisy result. In the general case, the notions of edge neighborhood and QL-edge neighborhood are the better alternatives in terms of privacy and utility. Although, there are indications that node neighborhood and QL-outedges neighborhood are considerable options for larger graphs, where the level of privacy for edge neighborhood and QL-edge neighborhood appears to be negligible based on utility measurements.

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Hussein, Mudhafar Saber. « Modelling and analysing adaptive networks : from graph transformation system to ordinary differential equation ». Thesis, University of Leicester, 2017. http://hdl.handle.net/2381/40123.

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Online social networks pose particular challenges to designing effective algorithms and protocols. Apart from their distributed nature, their behaviour depends on user behaviour and is difficult to test at a realistic scale. Stochastic graph transformation systems can model the operation of such networks but due to the inherent complexity they are hard to analyse. Techniques such as model checking and simulation, which can be used to verify a range of quantitative properties, do not scale well to systems with large graphs and state spaces. Aiming for an efficient alternative, we propose to derive a system of differential equations approximating the average evolution of the network. Variables in these equations represent numbers of occurrences of patterns selected to observe structural features. To keep the number of patterns small, rather than aiming for a fully accurate model we approximate complex patterns by the composition of simpler ones. We describe the approximation and its implementation based on critical pair analysis, illustrate and validate the process by examples of a social network protocol for P2P content policing and a voter model. We will also point out limitations in our approach to approximation and the use of differential equations more generally and discuss how they can be overcome.

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Nguyen, Huu-Hiep. « Social Graph Anonymization ». Thesis, Université de Lorraine, 2016. http://www.theses.fr/2016LORR0168/document.

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La vie privée est une préoccupation des utilisateurs des réseaux sociaux. Les réseaux sociaux sont une source de données précieuses pour des analyses scientifiques ou commerciales. Cette thèse aborde trois problèmes de confidentialité des réseaux sociaux: l'anonymisation de graphes sociaux, la détection de communautés privées et l'échange de liens privés. Nous abordons le problème d'anonymisation de graphes via la sémantique de l'incertitude et l'intimité différentielle. Pour la première, nous proposons un modèle général appelé Uncertain Adjacency Matrix (UAM) qui préserve dans le graphe anonymisé les degrés des nœuds du graphe non-anonymisé. Nous analysons deux schémas proposés récemment et montrons leur adaptation dans notre modèle. Nous aussi présentons notre approche dite MaxVar. Pour la technique d'intimité différentielle, le problème devient difficile en raison de l'énorme espace des graphes anonymisés possibles. Un grand nombre de systèmes existants ne permettent pas de relâcher le budget contrôlant la vie privée, ni de déterminer sa borne supérieure. Dans notre approche nous pouvons calculer cette borne. Nous introduisons le nouveau schéma Top-m-Filter de complexité linéaire et améliorons la technique récente EdgeFlip. L'évaluation de ces algorithmes sur une large gamme de graphes donne un panorama de l'état de l'art. Nous présentons le problème original de la détection de la communauté dans le cadre de l'intimité différentielle. Nous analysons les défis majeurs du problème et nous proposons quelques approches pour les aborder sous deux angles: par perturbation d'entrée (schéma LouvainDP) et par perturbation d'algorithme (schéma ModDivisive)
Privacy is a serious concern of users in daily usage of social networks. Social networks are a valuable data source for large-scale studies on social organization and evolution and are usually published in anonymized forms. This thesis addresses three privacy problems of social networks: graph anonymization, private community detection and private link exchange. First, we tackle the problem of graph anonymization via uncertainty semantics and differential privacy. As for uncertainty semantics, we propose a general obfuscation model called Uncertain Adjacency Matrix (UAM) that keep expected node degrees equal to those in the unanonymized graph. We analyze two recently proposed schemes and show their fitting into the model. We also present our scheme Maximum Variance (MaxVar) to fill the gap between them. Using differential privacy, the problem is very challenging because of the huge output space of noisy graphs. A large body of existing schemes on differentially private release of graphs are not consistent with increasing privacy budgets as well as do not clarify the upper bounds of privacy budgets. In this thesis, such a bound is provided. We introduce the new linear scheme Top-m-Filter (TmF) and improve the existing technique EdgeFlip. Thorough comparative evaluation on a wide range of graphs provides a panorama of the state-of-the-art's performance as well as validates our proposed schemes. Second, we present the problem of community detection under differential privacy. We analyze the major challenges behind the problem and propose several schemes to tackle them from two perspectives: input perturbation (LouvainDP) and algorithm perturbation (ModDivisive)

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Eisenack, Klaus. « Model ensembles for natural resource management extensions of qualitative differential equations using graph theory and viability theory / ». [S.l.] : [s.n.], 2006. http://www.diss.fu-berlin.de/2006/326/index.html.

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Shang, Hui. « Privacy Preserving Kin Genomic Data Publishing ». Miami University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=miami1594835227299524.

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Hemmerling, Reinhard [Verfasser], Winfried [Akademischer Betreuer] Kurth, Robert [Akademischer Betreuer] Schaback et Paul-Henry [Akademischer Betreuer] Cournède. « Extending the Programming Language XL to Combine Graph Structures with Ordinary Differential Equations / Reinhard Hemmerling. Gutachter : Winfried Kurth ; Robert Schaback ; Paul-Henry Cournède. Betreuer : Winfried Kurth ». Göttingen : Niedersächsische Staats- und Universitätsbibliothek Göttingen, 2012. http://d-nb.info/1043023674/34.

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Qing, Yulan S. M. Massachusetts Institute of Technology. « Differential posets and dual graded graphs ». Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/47899.

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Thesis (S. M.)--Massachusetts Institute of Technology, Dept. of Mathematics, 2008.
Includes bibliographical references (leaf 53).
In this thesis I study r-differential posets and dual graded graphs. Differential posets are partially ordered sets whose elements form the basis of a vector space that satisfies DU-UD=rI, where U and D are certain order-raising and order-lowering operators. New results are presented related to the growth and classification of differential posets. In particular, we prove that the rank sequence of an r-differential poset is bounded above by the Fibonacci sequence and that there is a unique poset with such a maximum rank sequence. We also prove that a 1-differential lattice is either Young's lattice or the Fibonacci lattice. In the second part of the thesis, we present a series of new examples of dual graded graphs that are not isomorphic to the ones presented in Fomin's original paper.
by Yulan Qing.
S.M.

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Livres sur le sujet "Differential Graph"

1962-, Bernard Lucas, et Roux François 1960-, dir. Emerging topics on differential geometry and graph theory. Hauppauge, NY : Nova Science Publishers, 2009.

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Deo, Naokant, Vijay Gupta, Ana Maria Acu et P. N. Agrawal, dir. Mathematical Analysis II : Optimisation, Differential Equations and Graph Theory. Singapore : Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1157-8.

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Sunada, Toshikazu. Topological Crystallography : With a View Towards Discrete Geometric Analysis. Tokyo : Springer Japan, 2013.

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Olsen, Lars. Random geometrically graph directed self-similar multifractals. Harlow, Essex, England : Longman Scientific & Technical, 1994.

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K, Böröczky, Tóth G. Fejes, Bolyai János Matematikai Tarsulat et International Conference on Intuitive Geometry (1985 : Siófok, Hungary), dir. Intuitive geometry. Amsterdam : North-Holland, 1987.

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service), SpringerLink (Online, dir. Discrete Groups, Expanding Graphs and Invariant Measures. Basel : Birkhäuser Basel, 2010.

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Josef, Leydold, et Stadler Peter F. 1965-, dir. Laplacian eigenvectors of graphs : Perron-Frobenius and Faber-Krahn type theorems. Berlin : Springer, 2007.

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Seslavin, Andrey. Theory of automatic control. Linear, continuous systems. ru : INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1014654.

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The textbook presents the basics of the classical theory of automatic control, based on mathematical models of real systems, given in the form of systems of linear differential equations with constant coefficients. Methods based on Laplace and Fourier transforms, stability, controllability, and observability theory, as well as directed graph theory and linear algebra are used. Meets the requirements of the federal state educational standards of higher education of the latest generation. For students of higher educational institutions studying in the areas of training and specialties 15.00.00 "Mechanical Engineering", 27.00.00 "Management in technical systems".

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Zhukova, Galina, et Margarita Rushaylo. Mathematical analysis in examples and tasks. Part 1. ru : INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1072156.

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The purpose of the textbook is to help students to master basic concepts and research methods used in mathematical analysis. In part 1 of the proposed cycle of workshops on the following topics: theory of sets, theory of limits, theory of continuous functions; differential calculus of functions of one variable, its application to the study of the properties of functions and graph; integral calculus of functions of one variable: indefinite, definite, improper integrals; hyperbolic functions; applications of integral calculus to the analysis and solution of practical problems. For the development of each topic the necessary theoretical and background material, reviewed a large number of examples with detailed analysis and solutions, the options for independent work. For self-training and quality control of the obtained knowledge provides exercises and problems with answers and guidance. For teachers, students and postgraduate students studying advanced mathematics.

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Ocneanu, Adrian. Quantum symmetry, differential geometry of finite graphs and classification of subfactors. Tokyo, Japan : Dept. of Mathematics, University of Tokyo, 1991.

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Chapitres de livres sur le sujet "Differential Graph"

Hu, Yifan, Stephen Kobourov et Sankar Veeramoni. « On Maximum Differential Graph Coloring ». Dans Graph Drawing, 274–86. Berlin, Heidelberg : Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18469-7_25.

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Pushpam, P. Roushini Leely, et D. Yokesh. « Restrained Differential of a Graph ». Dans Theoretical Computer Science and Discrete Mathematics, 332–40. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64419-6_43.

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Koenderink, Jan J. « Isotropic Differential Geometry in Graph Spaces ». Dans Computer Vision, 429–33. Boston, MA : Springer US, 2014. http://dx.doi.org/10.1007/978-0-387-31439-6_780.

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Koenderink, Jan J. « Isotropic Differential Geometry in Graph Spaces ». Dans Computer Vision, 715–18. Cham : Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63416-2_780.

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Wang, Yue, Xintao Wu et Leting Wu. « Differential Privacy Preserving Spectral Graph Analysis ». Dans Advances in Knowledge Discovery and Data Mining, 329–40. Berlin, Heidelberg : Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37456-2_28.

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Upadhyay, Jalaj. « Random Projections, Graph Sparsification, and Differential Privacy ». Dans Advances in Cryptology - ASIACRYPT 2013, 276–95. Berlin, Heidelberg : Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-42033-7_15.

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Vasilyeva, Elena, Maik Thiele, Christof Bornhövd et Wolfgang Lehner. « Top-k Differential Queries in Graph Databases ». Dans Advances in Databases and Information Systems, 112–25. Cham : Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10933-6_9.

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Yin, Yiping, Qing Liao, Yang Liu et Ruifeng Xu. « Structural-Based Graph Publishing Under Differential Privacy ». Dans Cognitive Computing – ICCC 2019, 67–78. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23407-2_6.

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Nguyen, Binh P., Hoa Ngo, Jihun Kim et Jong Kim. « Publishing Graph Data with Subgraph Differential Privacy ». Dans Information Security Applications, 134–45. Cham : Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31875-2_12.

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Finn, Robert. « The inclination of an H-graph ». Dans Calculus of Variations and Partial Differential Equations, 40–60. Berlin, Heidelberg : Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/bfb0082884.

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Actes de conférences sur le sujet "Differential Graph"

Yang, Carl, Haonan Wang, Ke Zhang, Liang Chen et Lichao Sun. « Secure Deep Graph Generation with Link Differential Privacy ». Dans Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California : International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/450.

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Many data mining and analytical tasks rely on the abstraction of networks (graphs) to summarize relational structures among individuals (nodes). Since relational data are often sensitive, we aim to seek effective approaches to generate utility-preserved yet privacy-protected structured data. In this paper, we leverage the differential privacy (DP) framework to formulate and enforce rigorous privacy constraints on deep graph generation models, with a focus on edge-DP to guarantee individual link privacy. In particular, we enforce edge-DP by injecting designated noise to the gradients of a link reconstruction based graph generation model, while ensuring data utility by improving structure learning with structure-oriented graph discrimination. Extensive experiments on two real-world network datasets show that our proposed DPGGAN model is able to generate graphs with effectively preserved global structure and rigorously protected individual link privacy.

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Deur, Josˇko, Matthew Hancock et Francis Assadian. « Bond Graph Modeling and Analysis of Active Differential Kinematics ». Dans ASME 2008 Dynamic Systems and Control Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/dscc2008-2285.

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This paper describes the kinematic structures of Active Limited Slip Differential (ALSD) and different concepts of Torque Vectoring Differentials (TVD) (superposition clutch concept, stationary clutch concept, and 4WD concept). The bond graph method is used to derive the models of ALSD/TVD kinematics. Based on the developed models, a comparative analysis of active differential operating modes and performance is conducted.

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Xu, Depeng, Shuhan Yuan et Xintao Wu. « Differential Privacy Preserving Causal Graph Discovery ». Dans 2017 IEEE Symposium on Privacy-Aware Computing (PAC). IEEE, 2017. http://dx.doi.org/10.1109/pac.2017.24.

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Fister, Iztok, et Janez Brest. « Using differential evolution for the graph coloring ». Dans 2011 IEEE Symposium On Differential Evolution - Part Of 17273 - 2011 Ssci. IEEE, 2011. http://dx.doi.org/10.1109/sde.2011.5952075.

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Lu, Wentian, et Gerome Miklau. « Exponential random graph estimation under differential privacy ». Dans KDD '14 : The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA : ACM, 2014. http://dx.doi.org/10.1145/2623330.2623683.

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Shen, Entong, et Ting Yu. « Mining frequent graph patterns with differential privacy ». Dans KDD' 13 : The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA : ACM, 2013. http://dx.doi.org/10.1145/2487575.2487601.

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Wang, Zhengyi, Zhongkai Hao, Ziqiao Wang, Hang Su et Jun Zhu. « Cluster Attack : Query-based Adversarial Attacks on Graph with Graph-Dependent Priors ». Dans Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California : International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/108.

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While deep neural networks have achieved great success in graph analysis, recent work has shown that they are vulnerable to adversarial attacks. Compared with adversarial attacks on image classification, performing adversarial attacks on graphs is more challenging because of the discrete and non-differential nature of the adjacent matrix for a graph. In this work, we propose Cluster Attack --- a Graph Injection Attack (GIA) on node classification, which injects fake nodes into the original graph to degenerate the performance of graph neural networks (GNNs) on certain victim nodes while affecting the other nodes as little as possible. We demonstrate that a GIA problem can be equivalently formulated as a graph clustering problem; thus, the discrete optimization problem of the adjacency matrix can be solved in the context of graph clustering. In particular, we propose to measure the similarity between victim nodes by a metric of Adversarial Vulnerability, which is related to how the victim nodes will be affected by the injected fake node, and to cluster the victim nodes accordingly. Our attack is performed in a practical and unnoticeable query-based black-box manner with only a few nodes on the graphs that can be accessed. Theoretical analysis and extensive experiments demonstrate the effectiveness of our method by fooling the node classifiers with only a small number of queries.

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Deur, Josˇko, Matthew Hancock et Francis Assadian. « Modeling of Active Differential Dynamics ». Dans ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-69248.

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Active differentials are increasingly being used in high-end vehicles in order to improve the overall performance of vehicle dynamics control systems. The active differentials can be divided into active limited slip differentials and torque vectoring differentials. This paper presents the development of a generalized mathematical model of active differential dynamics using the bond graph modeling technique. Different levels of model complexity are considered, starting from a second-order model with lumped input and output inertia towards high order models including the gear inertia and halfshaft compliance. The paper also presents typical model simulation results and their comparative analysis with respect to drivability and time response features.

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Jin, Hongwei, et Xun Chen. « Gromov-Wasserstein Discrepancy with Local Differential Privacy for Distributed Structural Graphs ». Dans Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California : International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/294.

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Learning the similarity between structured data, especially the graphs, is one of the essential problems. Besides the approach like graph kernels, Gromov-Wasserstein (GW) distance recently draws a big attention due to its flexibility to capture both topological and feature characteristics, as well as handling the permutation invariance. However, structured data are widely distributed for different data mining and machine learning applications. With privacy concerns, accessing the decentralized data is limited to either individual clients or different silos. To tackle these issues, we propose a privacy-preserving framework to analyze the GW discrepancy of node embedding learned locally from graph neural networks in a federated flavor, and then explicitly place local differential privacy (LDP) based on Multi-bit Encoder to protect sensitive information. Our experiments show that, with strong privacy protection guaranteed by ε-LDP algorithm, the proposed framework not only preserves privacy in graph learning, but also presents a noised structural metric under GW distance, resulting in comparable and even better performance in classification and clustering tasks. Moreover, we reason the rationale behind the LDP-based GW distance analytically and empirically.

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Zhang, Zaixi, Qi Liu, Zhenya Huang, Hao Wang, Chengqiang Lu, Chuanren Liu et Enhong Chen. « GraphMI : Extracting Private Graph Data from Graph Neural Networks ». Dans Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California : International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/516.

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As machine learning becomes more widely used for critical applications, the need to study its implications in privacy becomes urgent. Given access to the target model and auxiliary information, model inversion attack aims to infer sensitive features of the training dataset, which leads to great privacy concerns. Despite its success in the grid domain, directly applying model inversion techniques on non grid domains such as graph achieves poor attack performance due to the difficulty to fully exploit the intrinsic properties of graphs and attributes of graph nodes used in GNN models. To bridge this gap, we present Graph Model Inversion attack, which aims to infer edges of the training graph by inverting Graph Neural Networks, one of the most popular graph analysis tools. Specifically, the projected gradient module in our method can tackle the discreteness of graph edges while preserving the sparsity and smoothness of graph features. Moreover, a well designed graph autoencoder module can efficiently exploit graph topology, node attributes, and target model parameters. With the proposed method, we study the connection between model inversion risk and edge influence and show that edges with greater influence are more likely to be recovered. Extensive experiments over several public datasets demonstrate the effectiveness of our method. We also show that differential privacy in its canonical form can hardly defend our attack while preserving decent utility.

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Rapports d'organisations sur le sujet "Differential Graph"

Or, Etti, Tai-Ping Sun, Amnon Lichter et Avichai Perl. Characterization and Manipulation of the Primary Components in Gibberellin Signaling in the Grape Berry. United States Department of Agriculture, janvier 2010. http://dx.doi.org/10.32747/2010.7592649.bard.

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Seedless cultivars dominate the table grape industry. In these cultivars it is mandatory to apply gibberellin (GA) to stimulate berry development to a commercially acceptable size. These cultivars differ in their sensitivity to GA application, and it frequently results in adverse effects such as decreased bud fertility and increased fruit drop. Our long term goals are to (1) understand the molecular basis for the differential sensitivity and identify markers for selection of sensitive cultivars (2) to develop new strategies for targeted manipulation of the grape berry response to GA that will eliminate the need in GA application and the undesirable effects of GA on the vine, while maintaining its desirable effects on the berry. Both strategies are expected to reduce production cost and meet growing consumer demand for reduced use of chemicals. This approach relies on a comprehensive characterization of the central components in the GA signaling cascade in the berry. Several key components in the GA signaling pathway were identified in Arabidopsis and rice, including the GA receptors, GID1s, and a family of DELLA proteins that are the major negative regulators of the GA response. GA activates its response pathway by binding to GID1s, which then target DELLAs for degradation via interaction with SLY, a DELLA specific F-box protein. In grape, only one DELLA gene was characterized prior to this study, which plays a major role in inhibiting GA-promoted stem growth and GA-repressed floral induction but it does not regulate fruit growth. Therefore, we speculated that other DELLA family member(s) may control GA responses in berry, and their identification and manipulation may result in GA-independent berry growth. In the current study we isolated two additional VvDELLA family members, two VvGID1 genes and two VvSLY genes. Arabidopsis anti-AtRGA polyclonal antibodies recognized all three purified VvDELLA proteins, but its interaction with VvDELLA3 was weaker. Overexpression of the VvDELLAs, the VvGID1s, and the VvSLYs in the Arabidopsis mutants ga1-3/rga-24, gid1a-2/1c-2 and sly1-10, respectively, rescued the various mutant phenotypes. In vitro GAdependent physical interaction was shown between the VvDELLAs and the VvGID1s, and GAindependent interaction was shown between the VvDELLAs and VvSLYs. Interestingly, VvDELLA3 did not interact with VvGID1b. Together, the results indicate that the identified grape homologs serve as functional DELLA repressors, receptors and DELLA-interacting F-box proteins. Expression analyses revealed that (1) VvDELLA2 was expressed in all the analyzed tissues and was the most abundant (2) VvDELLA1 was low expressed in berries, confirming former study (3) Except in carpels and very young berries, VvDELLA3 levels were the lowest in most tissues. (4) Expression of both VvGID1s was detected in all the grape tissues, but VvGID1b transcript levels were significantly higher than VvGID1a. (5) In general, both VvDELLAs and VvGID1s transcripts levels increased as tissues aged. Unfertilized and recently fertilized carpels did not follow this trend, suggesting different regulatory mechanism of GA signaling in these stages. Characterization of the response to GA of various organs in three seedless cultivars revealed differential response of the berries and rachis. Interestingly, VvDELLA3 transcript levels in the GA-unresponsive berries of cv. Spring blush were significantly higher compared to their levels in the highly responsive berries of cv. Black finger. Assuming that VvDELLA2 and VvDELLA3 are regulating berry size, constructs carrying potential dominant mutations in each gene were created. Furthermore, constitutive silencing of these genes by mIR is underway, to reveal the effect of each gene on the berry phenotype.

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Or, Etti, David Galbraith et Anne Fennell. Exploring mechanisms involved in grape bud dormancy : Large-scale analysis of expression reprogramming following controlled dormancy induction and dormancy release. United States Department of Agriculture, décembre 2002. http://dx.doi.org/10.32747/2002.7587232.bard.

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The timing of dormancy induction and release is very important to the economic production of table grape. Advances in manipulation of dormancy induction and dormancy release are dependent on the establishment of a comprehensive understanding of biological mechanisms involved in bud dormancy. To gain insight into these mechanisms we initiated the research that had two main objectives: A. Analyzing the expression profiles of large subsets of genes, following controlled dormancy induction and dormancy release, and assessing the role of known metabolic pathways, known regulatory genes and novel sequences involved in these processes B. Comparing expression profiles following the perception of various artificial as well as natural signals known to induce dormancy release, and searching for gene showing similar expression patterns, as candidates for further study of pathways having potential to play a central role in dormancy release. We first created targeted EST collections from V. vinifera and V. riparia mature buds. Clones were randomly selected from cDNA libraries prepared following controlled dormancy release and controlled dormancy induction and from respective controls. The entire collection (7920 vinifera and 1194 riparia clones) was sequenced and subjected to bioinformatics analysis, including clustering, annotations and GO classifications. PCR products from the entire collection were used for printing of cDNA microarrays. Bud tissue in general, and the dormant bud in particular, are under-represented within the grape EST database. Accordingly, 59% of the our vinifera EST collection, composed of 5516 unigenes, are not included within the current Vitis TIGR collection and about 22% of these transcripts bear no resemblance to any known plant transcript, corroborating the current need for our targeted EST collection and the bud specific cDNA array. Analysis of the V. riparia sequences yielded 814 unigenes, of which 140 are unique (keilin et al., manuscript, Appendix B). Results from computational expression profiling of the vinifera collection suggest that oxidative stress, calcium signaling, intracellular vesicle trafficking and anaerobic mode of carbohydrate metabolism play a role in the regulation and execution of grape-bud dormancy release. A comprehensive analysis confirmed the induction of transcription from several calcium–signaling related genes following HC treatment, and detected an inhibiting effect of calcium channel blocker and calcium chelator on HC-induced and chilling-induced bud break. It also detected the existence of HC-induced and calcium dependent protein phosphorylation activity. These data suggest, for the first time, that calcium signaling is involved in the mechanism of dormancy release (Pang et al., in preparation). We compared the effects of heat shock (HS) to those detected in buds following HC application and found that HS lead to earlier and higher bud break. We also demonstrated similar temporary reduction in catalase expression and temporary induction of ascorbate peroxidase, glutathione reductase, thioredoxin and glutathione S transferase expression following both treatments. These findings further support the assumption that temporary oxidative stress is part of the mechanism leading to bud break. The temporary induction of sucrose syntase, pyruvate decarboxylase and alcohol dehydrogenase indicate that temporary respiratory stress is developed and suggest that mitochondrial function may be of central importance for that mechanism. These finding, suggesting triggering of identical mechanisms by HS and HC, justified the comparison of expression profiles of HC and HS treated buds, as a tool for the identification of pathways with a central role in dormancy release (Halaly et al., in preparation). RNA samples from buds treated with HS, HC and water were hybridized with the cDNA arrays in an interconnected loop design. Differentially expressed genes from the were selected using R-language package from Bioconductor project called LIMMA and clones showing a significant change following both HS and HC treatments, compared to control, were selected for further analysis. A total of 1541 clones show significant induction, of which 37% have no hit or unknown function and the rest represent 661 genes with identified function. Similarly, out of 1452 clones showing significant reduction, only 53% of the clones have identified function and they represent 573 genes. The 661 induced genes are involved in 445 different molecular functions. About 90% of those functions were classified to 20 categories based on careful survey of the literature. Among other things, it appears that carbohydrate metabolism and mitochondrial function may be of central importance in the mechanism of dormancy release and studies in this direction are ongoing. Analysis of the reduced function is ongoing (Appendix A). A second set of hybridizations was carried out with RNA samples from buds exposed to short photoperiod, leading to induction of bud dormancy, and long photoperiod treatment, as control. Analysis indicated that 42 genes were significant difference between LD and SD and 11 of these were unique.

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Friedman, Haya, Julia Vrebalov et James Giovannoni. Elucidating the ripening signaling pathway in banana for improved fruit quality, shelf-life and food security. United States Department of Agriculture, octobre 2014. http://dx.doi.org/10.32747/2014.7594401.bard.

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Background : Banana being a monocot and having distinct peel and pulp tissues is unique among the fleshy fruits and hence can provide a more comprehensive understanding of fruit ripening. Our previous research which translated ripening discoveries from tomato, led to the identification of six banana fruit-associated MADS-box genes, and we confirmed the positive role of MaMADS1/2 in banana ripening. The overall goal was to further elucidate the banana ripening signaling pathway as mediated by MADS-boxtranscriptional regulators. Specific objectives were: 1) characterize transcriptional profiles and quality of MaMADS1/2 repressed fruit; 2) reveal the role of additional MaMADSgenes in ripening; 3) develop a model of fruit MaMADS-box mode of action; and 4) isolate new components of the banana ripening signaling pathway. Major conclusion: The functions of the banana MaMADS1-5 have been examined by complimenting the rinor the TAGL1-suppressed lines of tomato. Only MaMADS5 exhibited partial complementation of TAGL1-suppressed and rinlines, suggesting that while similar genes play corresponding roles in ripening, evolutionary divergence makes heterologous complementation studies challenging. Nevertheless, the partial complementation of tomato TAGL1-surpessed and rinlines with MaMADS5 suggests this gene is likely an important ripening regulator in banana, worthy of further study. RNA-seqtranscriptome analysis during ripening was performed on WT and MaMADS2-suppressed lines revealing additional candidate genes contributing to ripening control mechanisms. In summary, we discovered 39 MaMADS-box genes in addition to homologues of CNR, NOR and HB-1 expressed in banana fruits, and which were shown in tomato to play necessary roles in ripening. For most of these genes the expression in peel and pulp was similar. However, a number of key genes were differentially expressed between these tissues indicating that the regulatory components which are active in peel and pulp include both common and tissue-specific regulatory systems, a distinction as compared to the more uniform tomato fruit pericarp. Because plant hormones are well documented to affect fruit ripening, the expressions of genes within the auxin, gibberellin, abscisic acid, jasmonic acid, salicylic and ethylene signal transduction and synthesis pathways were targeted in our transcriptome analysis. Genes’ expression associated with these pathways generally declined during normal ripening in both peel and pulp, excluding cytokinin and ethylene, and this decline was delayed in MaMADS2-suppressed banana lines. Hence, we suggest that normal MaMADS2 activity promotes the observed downward expression within these non-ethylene pathways (especially in the pulp), thus enabling ripening progression. In contrast, the expressions of ACSand ACOof the ethylene biosynthesis pathway increase in peel and pulp during ripening and are delayed/inhibited in the transgenic bananas, explaining the reduced ethylene production of MaMADS2-suppressed lines. Inferred by the different genes’ expression in peel and pulp of the gibberellins, salicylic acid and cytokinins pathways, it is suggested that hormonal regulation in these tissues is diverse. These results provide important insights into possible avenues of ripening control in the diverse fruit tissues of banana which was not previously revealed in other ripening systems. As such, our transcriptome analysis of WT and ripening delayed banana mutants provides a starting point for further characterization of ripening. In this study we also developed novel evidence that the cytoskeleton may have a positive role in ripening as components of this pathway were down-regulated by MaMADS2 suppression. The mode of cytoskeleton involvement in fruit ripening remains unclear but presents a novel new frontier in ripening investigations. In summary, this project yielded functional understanding of the role and mode of action of MaMADS2 during ripening, pointing to both induction of ethylene and suppression of non-ethylene hormonal singling pathways. Furthermore, our data suggest important roles for cytoskeleton components and MaMADS5 in the overall banana ripening control network. Implications: The project revealed new molecular components/genes involved in banana ripening and refines our understanding of ripening responses in the peel and pulp tissues of this important species. This information is novel as compared to that derived from the more uniform carpel tissues of other highly studied ripening systems including tomato and grape. The work provides specific target genes for potential modification through genetic engineering or for exploration of useful genetic diversity in traditional breeding. The results from the project might point toward improved methods or new treatments to improve banana fruit storage and quality.

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