214,171 research outputs found
Structure fusion based on graph convolutional networks for semi-supervised classification
Suffering from the multi-view data diversity and complexity for
semi-supervised classification, most of existing graph convolutional networks
focus on the networks architecture construction or the salient graph structure
preservation, and ignore the the complete graph structure for semi-supervised
classification contribution. To mine the more complete distribution structure
from multi-view data with the consideration of the specificity and the
commonality, we propose structure fusion based on graph convolutional networks
(SF-GCN) for improving the performance of semi-supervised classification.
SF-GCN can not only retain the special characteristic of each view data by
spectral embedding, but also capture the common style of multi-view data by
distance metric between multi-graph structures. Suppose the linear relationship
between multi-graph structures, we can construct the optimization function of
structure fusion model by balancing the specificity loss and the commonality
loss. By solving this function, we can simultaneously obtain the fusion
spectral embedding from the multi-view data and the fusion structure as
adjacent matrix to input graph convolutional networks for semi-supervised
classification. Experiments demonstrate that the performance of SF-GCN
outperforms that of the state of the arts on three challenging datasets, which
are Cora,Citeseer and Pubmed in citation networks
Mapping Fusion and Synchronized Hyperedge Replacement into Logic Programming
In this paper we compare three different formalisms that can be used in the
area of models for distributed, concurrent and mobile systems. In particular we
analyze the relationships between a process calculus, the Fusion Calculus,
graph transformations in the Synchronized Hyperedge Replacement with Hoare
synchronization (HSHR) approach and logic programming. We present a translation
from Fusion Calculus into HSHR (whereas Fusion Calculus uses Milner
synchronization) and prove a correspondence between the reduction semantics of
Fusion Calculus and HSHR transitions. We also present a mapping from HSHR into
a transactional version of logic programming and prove that there is a full
correspondence between the two formalisms. The resulting mapping from Fusion
Calculus to logic programming is interesting since it shows the tight analogies
between the two formalisms, in particular for handling name generation and
mobility. The intermediate step in terms of HSHR is convenient since graph
transformations allow for multiple, remote synchronizations, as required by
Fusion Calculus semantics.Comment: 44 pages, 8 figures, to appear in a special issue of Theory and
Practice of Logic Programming, minor revisio
Unsupervised Visual and Textual Information Fusion in Multimedia Retrieval - A Graph-based Point of View
Multimedia collections are more than ever growing in size and diversity.
Effective multimedia retrieval systems are thus critical to access these
datasets from the end-user perspective and in a scalable way. We are interested
in repositories of image/text multimedia objects and we study multimodal
information fusion techniques in the context of content based multimedia
information retrieval. We focus on graph based methods which have proven to
provide state-of-the-art performances. We particularly examine two of such
methods : cross-media similarities and random walk based scores. From a
theoretical viewpoint, we propose a unifying graph based framework which
encompasses the two aforementioned approaches. Our proposal allows us to
highlight the core features one should consider when using a graph based
technique for the combination of visual and textual information. We compare
cross-media and random walk based results using three different real-world
datasets. From a practical standpoint, our extended empirical analysis allow us
to provide insights and guidelines about the use of graph based methods for
multimodal information fusion in content based multimedia information
retrieval.Comment: An extended version of the paper: Visual and Textual Information
Fusion in Multimedia Retrieval using Semantic Filtering and Graph based
Methods, by J. Ah-Pine, G. Csurka and S. Clinchant, submitted to ACM
Transactions on Information System
Fusion of Dilute Lattice Models
The fusion procedure is implemented for the dilute lattice models and a
fusion hierarchy of functional equations with an structure is derived
for the fused transfer matrices. We also present the Bethe ansatz equations for
the dilute lattice models and discuss their connection with the fusion
hierarchy. The solution of the fusion hierarchy for the eigenvalue spectra of
the dilute lattice models will be presented in a subsequent paper.Comment: 45 pages; Latex file; epsf.tex needed for graph
Integrable Boundaries, Conformal Boundary Conditions and A-D-E Fusion Rules
The minimal theories are labelled by a Lie algebra pair where
is of -- type. For these theories on a cylinder we conjecture a
complete set of conformal boundary conditions labelled by the nodes of the
tensor product graph . The cylinder partition functions are given
by fusion rules arising from the graph fusion algebra of . We
further conjecture that, for each conformal boundary condition, an integrable
boundary condition exists as a solution of the boundary Yang-Baxter equation
for the associated lattice model. The theory is illustrated using the
or 3-state Potts model.Comment: 4 pages, REVTe
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