Auflistung nach Autor/inAuflistung nach Autor/in "Riesen, Kaspar"
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A Family of Novel Graph Kernels for Structural Pattern Recognition.
Bunke, Horst; Riesen, Kaspar (2007-01-01) -
A Fast Matching Algorithm for Graph-Based Handwriting Recognition.
Fischer, Andreas; Suen, Ching Y; Frinken, Volkmar; Riesen, Kaspar; Bunke, Horst (2013-01-01) -
A First Step Towards Exact Graph Edit Distance Using Bipartite Graph Matching
Ferrer, Miquel; Serratosa, Francesco; Riesen, Kaspar (Springer, 2015)In recent years, a powerful approximation framework for graph edit distance computation has been introduced. This particular approximation is based on an optimal assignment of local graph structures which can be established ... -
A Graph-Based Recommender for Enhancing the Assortment of Web Shops
Riesen, Kaspar; Witschel, Hans Friedrich; Galie, E. (2015)In this work, we consider a situation where multiple Providers (competitors) serve a common market, using a common infrastructure of sales channels. More speci cally, we focus on multiple web shops that are run by the same ... -
A Novel Software Toolkit for Graph Edit Distance Computation.
Riesen, Kaspar; Emmenegger, Sandro; Bunke, Horst (2013-05-17) -
An Approximate Algorithm for Median Graph Computation using Graph Embedding.
Ferrer, Miguel; Valveny, Ernest; Serratosa, Francesco; Riesen, Kaspar; Bunke, Horst (2008-01-01) -
An Experimental Study of Graph Classification using Prototype Selection.
Fischer, Andreas; Riesen, Kaspar; Bunke, Horst (2008-01-01) -
Approximate Graph Edit Distance Computation by means of Bipartite Graph Matching.
Riesen, Kaspar; Bunke, Horst (2009-01-01) -
Approximation of graph edit distance based on Hausdorff matching.
Fischer, Andreas; Suen, Ching Y; Frinken, Volkmar; Riesen, Kaspar (2015-01-01) -
Approximation of Graph Edit Distance in Quadratic Time
Riesen, Kaspar; Ferrer, Miquel; Fischer, Andreas; Bunke, Horst (2015-05)The basic idea of a recent graph matching framework is to reduce the problem of graph edit distance (GED) to an instance of a linear sum assignment problem (LSAP). The optimal solution for this simplified GED problem can ... -
Bipartite Graph Matching for Computing the Edit Distance of Graphs.
Riesen, Kaspar; Neuhaus, Michel; Bunke, Horst (2007-01-01) -
Building Classifier Ensembles Using Greedy Graph Edit Distance
Riesen, Kaspar; Ferrer, Miquel; Fischer, Andreas (Springer, 2015)Classifier ensembles aim at more accurate classifications than single classifiers. In the present paper we introduce a general approach to building structural classifier ensembles, i.e. classifiers that make use of graphs ... -
Classification and Clustering of Vector Space Embedded Graphs.
Riesen, Kaspar; Bunke, Horst (2011-01-01) -
Classification and Clustering of Vector Space Embedded Graphs. Series in Machine Perception and Artificial Intelligence.
Riesen, Kaspar; Bunke, Horst (World Scientific, 2010-01-01) -
Classifier Ensembles for Vector Space Embedding of Graphs.
Riesen, Kaspar; Bunke, Horst (2007-01-01) -
Clinical risk management in hospitals: Strategy, central coordination and dialogue as key enablers.
Riesen, Kaspar; Gaüzère, Benoit; Bougleux, Sébastien; Brun, Luc (2014-08-22) -
Cluster Ensembles based on Vector Space Embeddings of Graphs.
Riesen, Kaspar; Bunke, Horst (LNCS 5519, 2009-01-01) -
Combining Bipartite Graph Matching and Beam Search for Graph Edit Distance Approximation
Riesen, Kaspar; Fischer, Andreas; Bunke, Horst (Springer, 2014)Graph edit distance (GED) is a powerful and flexible graph dissimilarity model. Yet, exact computation of GED is an instance of a quadratic assignment problem and can thus be solved in exponential time complexity only. A ... -
Combining Bipartite Graph Matching and Beam Search for Graph Edit Distance Approximation.
Riesen, Kaspar; Bunke, Horst; Fischer, Andreas (2014-01-01) -
Computing Upper and Lower Bounds of Graph Edit Distance in Cubic Time
Riesen, Kaspar; Fischer, Andreas; Bunke, Horst (Springer, 2014)Exact computation of graph edit distance (GED) can be solved in exponential time complexity only. A previously introduced approximation framework reduces the computation of GED to an instance of a linear sum assignment ...