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Gillioz, Anthony; Riesen, Kaspar (2023). Graph-based pattern recognition on spectral reduced graphs. Pattern recognition, 144 Elsevier 10.1016/j.patcog.2023.109859
Gillioz, Anthony; Riesen, Kaspar (2023). Building Multiple Classifier Systems Using Linear Combinations of Reduced Graphs. SN computer science, 4(6), p. 743. Springer 10.1007/s42979-023-02194-1
Fuchs, Mathias; Riesen, Kaspar (2022). A novel way to formalize stable graph cores by using matching-graphs. Pattern recognition, 131 Elsevier 10.1016/j.patcog.2022.108846
Ferrer, M.; Valveny, E.; Serratosa, F.; Riesen, Kaspar; Bunke, Horst (2010). Generalized median graph computation by means of graph embedding in vector spaces. Pattern recognition, 43(4), pp. 1642-1655. Oxford: Pergamon 10.1016/j.patcog.2009.10.013
Neuhaus, Michel; Riesen, Kaspar; Bunke, Horst (2009). Novel kernels for error-tolerant graph classification. Spatial vision, 22(5), pp. 425-441. Leiden: Brill 10.1163/156856809789476119
Riesen, Kaspar; Bunke, Horst (2009). Reducing the dimensionality of dissimilarity space embedding graph kernels. Engineering applications of artificial intelligence, 22(1), pp. 48-56. Oxford: Pergamon 10.1016/j.engappai.2008.04.006
Riesen, Kaspar; Bunke, Horst (2009). Approximate graph edit distance computation by means of bipartite graph matching. Image and vision computing, 27(7), pp. 950-959. Amsterdam: Elsevier 10.1016/j.imavis.2008.04.004
Riesen, Kaspar; Bunke, Horst (2009). Graph classification by means of Lipschitz embedding. IEEE transactions on systems, man, and cybernetics. Part B - cybernetics, 39(6), pp. 1472-1483. New York, N.Y.: Institute of Electrical and Electronics Engineers IEEE 10.1109/TSMCB.2009.2019264
Gillioz, Anthony; Riesen, Kaspar (2022). Speeding up Graph Matching by Means of Systematic Graph Reductions Using Centrality Measures. In: 2022 12th International Conference on Pattern Recognition Systems (ICPRS). IEEE 10.1109/ICPRS54038.2022.9854062
Riesen, Kaspar; Jiang, Xiaoyi; Bunke, Horst (2010). Exact and inexact graph matching: methodology and applications. In: Aggarwal, Charu C.; Wang, Haixun (eds.) Managing and Mining Graph Data. Advances in database systems: Vol. 40 (pp. 217-247). Berlin-Heidelberg: Springer 10.1007/978-1-4419-6045-0_7
Bunke, Horst; Riesen, Kaspar (2009). Graph edit distance - optimal and suboptimal algorithms with application. In: Dehmer, Matthias; Emmert-Streib, Frank (eds.) Analysis of Complex Networks. From Biology to Linguistics (pp. 113-143). Chichester: John Wiley & Sons 10.1002/9783527627981.ch6
Riesen, Kaspar; Bunke, Horst (2009). Dissimilarity Based Vector Space Embedding of Graphs Using Prototype Reduction Schemes. In: Perner, Petra (ed.) Machine Learning and Data Mining in Pattern Recognition. 6th International Conference, MLDM 2009, Leipzig, Germany, July 23-25, 2009. Proceedings. Lecture Notes in Computer Science: Vol. 5632 (pp. 617-631). Heidelberg: Springer Verlag 10.1007/978-3-642-03070-3_47
Riesen, Kaspar; Fankhauser, Stefan; Bunke, Horst; Dickinson, Peter (2009). Efficient suboptimal graph isomorphism. In: Torsello, Andrea; Escolano, Francisco; Brun, Luc (eds.) Graph-Based Representations in Pattern Recognition 7th IAPR-TC-15 International Workshop, GbRPR 2009, Venice, Italy, May 26-28, 2009. Proceedings. Lecture Notes in Computer Science: Vol. 5534 (pp. 124-133). Heidelberg: Springer Verlag 10.1007/978-3-642-02124-4_13
Riesen, Kaspar; Bunke, Horst (2009). Feature ranking algorithms for improving classification of vector space embedded graphs. In: Jiang, Xiaoyi; Petkov, Nicolai (eds.) Computer Analysis of Images and Patterns 13th International Conference, CAIP 2009, Münster, Germany, September 2-4, 2009. Proceedings. Lecture Notes in Computer Science: Vol. 5702 (pp. 377-384). Heidelberg: Springer Verlag 10.1007/978-3-642-03767-2_46
Riesen, Kaspar; Bunke, Horst (2009). Cluster Ensembles Based on Vector Space Embeddings of Graphs. In: Proceedings Benediktsson, Jón Atli; Kittler, Josef; Roli, Fabio (eds.) Multiple Classifier Systems. 8th International Workshop, MCS 2009, Reykjavik, Iceland, June 10-12, 2009. Proceedings. Lecture Notes in Computer Science: Vol. 5519 (pp. 211-221). Heidelberg: Springer Verlag 10.1007/978-3-642-02326-2_22
Brügger, Alexandra; Bunke, Horst; Dickinson, Peter; Riesen, Kaspar (2008). Generalized Graph Matching for Data Mining and Information Retrieval. In: Perner, Petra (ed.) Advances in Data Mining. Medical Applications, E-Commerce, Marketing, and Theoretical Aspects 8th Industrial Conference, ICDM 2008 Leipzig, Germany, July 16-18, 2008 Proceedings. Lecture Notes in Computer Science: Vol. 5077 (pp. 298-312). Heidelberg: Springer Verlag 10.1007/978-3-540-70720-2_23
Riesen, K.; Bunke, H. (2008). Kernel k-Means Clustering Applied to Vector Space Embeddings of Graphs. In: Prevost, Lionel; Marinai, Simone; Schwenker, Friedhelm (eds.) Artificial Neural Networks in Pattern RecognitionThird IAPR Workshop, ANNPR 2008 Paris, France, July 2-4, 2008 Proceedings. Lecture Notes in Computer Science: Vol. 5064 (pp. 24-35). Heidelberg: Springer Verlag 10.1007/978-3-540-69939-2_3
Riesen, Kaspar; Bunke, Horst (2008). On Lipschitz Embeddings of Graphs. In: Lovrek, Ignac; Howlett, Robert; Jain, Lakhmi C. (eds.) Knowledge-Based Intelligent Information and Engineering Systems12th International Conference, KES 2008, Zagreb, Croatia, September 3-5, 2008, Proceedings, Part I. Lecture Notes in Computer Science: Vol. 5177 (pp. 131-140). Heidelberg: Springer Verlag 10.1007/978-3-540-85563-7_22
Bunke, Horst; Riesen, Kaspar (2008). Graph classification based on dissimilarity space embedding. In: da Vitoria Lobo, Niels; Kasparis, Takis; Roli, Fabio; Kwok, James T.; Georgiopoulos, Michael; Anagnostopoulos, Georgios C.; Loog, Marco (eds.) Structural, Syntactic, and Statistical Pattern Recognition. Joint IAPR International Workshop, SSPR & SPR 2008, Orlando, USA, December 4-6, 2008. Proceedings. Lecture Notes in Computer Science: Vol. 5342 (pp. 996-1007). Heidelberg: Springer Verlag 10.1007/978-3-540-89689-0_103
Riesen, Kaspar; Bunke, Horst (2008). IAM graph database repository for graph based pattern recognition and machine learning. In: da Vitoria Lobo, Niels; Kasparis, Takis; Roli, Fabio; Kwok, James T.; Georgiopoulos, Michael; Anagnostopoulos, Georgios C.; Loog, Marco (eds.) Structural, Syntactic, and Statistical Pattern Recognition. Joint IAPR International Workshop, SSPR & SPR 2008, Orlando, USA, December 4-6, 2008. Proceedings. Lecture Notes in Computer Science: Vol. 5342 (pp. 287-297). Heidelberg: Springer Verlag 10.1007/978-3-540-89689-0_33
Riesen, Kaspar; Bunke, Horst (2010). Graph Classification and Clustering Based on Vector Space Embedding. Series in machine perception and artificial intelligence: Vol. 77. Singapore: World Scientific Publishing
Jia, Linlin; Ning, Xiao; Gaüzère, Benoit; Honeine, Paul; Riesen, Kaspar (2023). Bridging Distinct Spaces in Graph-Based Machine Learning. In: Asian Conference on Pattern Recognition. Lecture Notes in Computer Science: Vol. 14407 (pp. 1-14). Cham: Springer 10.1007/978-3-031-47637-2_1
Gillioz, Anthony; Riesen, Kaspar (2023). Graph-Based vs. Vector-Based Classification: A Fair Comparison. In: International Workshop on Graph-Based Representations in Pattern Recognition. Lecture Notes in Computer Science: Vol. 14121 (pp. 25-34). Cham: Springer 10.1007/978-3-031-42795-4_3
Fankhauser, Benjamin; Bigler, Vidushi; Riesen, Kaspar (2023). Graph-Based Deep Learning on the Swiss River Network. In: International Workshop on Graph-Based Representations in Pattern Recognition. Lecture Notes in Computer Science: Vol. 14121 (pp. 172-181). Cham: Springer 10.1007/978-3-031-42795-4_16
Gillioz, Anthony; Riesen, Kaspar (2023). Two-Step Graph Classification on the Basis of Hierarchical Graphs. In: 12th International Conference on Pattern Recognition Applications and Methods 1 (pp. 296-303). SCITEPRESS - Science and Technology Publications 10.5220/0011657000003411
Masanti, Corina; Witschel, Hans-Friedrich; Riesen, Kaspar (2023). Novel Benchmark Data Set for Automatic Error Detection and Correction. In: International Conference on Applications of Natural Language to Information Systems. Lecture Notes in Computer Science: Vol. 13913 (pp. 511-521). Cham: Springer 10.1007/978-3-031-35320-8_38
Gillioz, Anthony; Riesen, Kaspar (2023). Graph Reduction Neural Networks for Structural Pattern Recognition. In: Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR). Lecture Notes in Computer Science: Vol. 13813 (pp. 64-73). Cham: Springer 10.1007/978-3-031-23028-8_7
Fuchs, Mathias; Riesen, Kaspar (2023). Matching-Graphs for Building Classification Ensembles. In: International Workshop on Graph-Based Representations in Pattern Recognition. Lecture Notes in Computer Science: Vol. 14121 (pp. 102-112). Cham: Springer 10.1007/978-3-031-42795-4_10
Gillioz, Anthony; Riesen, Kaspar (2022). Improving Graph Classification by Means of Linear Combinations of Reduced Graphs. In: 11th International Conference on Pattern Recognition Applications and Methods 1 (pp. 17-23). SCITEPRESS - Science and Technology Publications 10.5220/0010776900003122
Fuchs, Mathias; Riesen, Kaspar (2022). Graph Augmentation for Neural Networks Using Matching-Graphs. In: ANNPR 2022: Artificial Neural Networks in Pattern Recognition. Lecture Notes in Computer Science: Vol. 13739 (pp. 3-15). Cham: Springer 10.1007/978-3-031-20650-4_1
Fuchs, Mathias; Riesen, Kaspar (2022). Augment Small Training Sets Using Matching-Graphs. In: ICPRAI: International Conference on Pattern Recognition and Artificial Intelligence. Lecture Notes in Computer Science: Vol. 13364 (pp. 343-354). Cham: Springer 10.1007/978-3-031-09282-4_29
Fuchs, Mathias; Riesen, Kaspar (2022). Iterative Creation of Matching-Graphs - Finding Relevant Substructures in Graph Sets. In: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 25th Iberoamerican Congress, CIARP 2021. Lecture Notes in Computer Science: Vol. 12702 (pp. 382-391). Springer 10.1007/978-3-030-93420-0_36
Riesen, Kaspar; Witschel, Hans Friedrich; Grether, Loris (October 2021). Natural Language-based User Guidance for Knowledge Graph Exploration: A User Study (Unpublished). In: 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2021. Online. 25-27 October 2021.
Fuchs, Mathias; Riesen, Kaspar (2021). Graph Embedding in Vector Spaces Using Matching-Graphs. In: SISAP 2021 14th International Conference on Similarity Search and Applications, SISAP 2021. Lecture Notes in Computer Science: Vol. 13058 (pp. 352-363). Springer 10.1007/978-3-030-89657-7_26
Fuchs, Mathias; Riesen, Kaspar (2020). Matching of Matching-Graphs - A Novel Approach for Graph Classification. In: Proceedings of 2020 25th International Conference on Pattern Recognition (ICPR).
Richiardi, J.; Van de Ville, D.; Riesen, K.; Bunke, Horst (2010). Vector space embedding of undirected graphs with fixed-cardinality vertex sequences for classification. In: 20th International Conference on Pattern Recognition. Proceedings (pp. 902-905). Washington, DC: IEEE Computer Society 10.1109/icpr.2010.227
Fischer, Andreas; Riesen, Kaspar; Bunke, Horst (2010). Graph similarity features for HMM-based handwriting recognition in historical documents. In: 12th International Conference on Frontiers in Handwriting Recognition ICFHR 2010. 10.1109/icfhr.2010.47
Ferrer, M.; Valveny, E.; Serratosa, F.; Riesen, K.; Bunke, Horst (2008). An approximate algorithm for median graph computation using graph embedding. In: Proceedings of the 19th International Conference on Pattern Recognition, 8-11 December 2008, Tampa, FL (pp. 1-4). New York: Institute of Electrical and Electronics Engineers IEEE 10.1109/ICPR.2008.4761354
Fischer, A.; Riesen, K.; Bunke, H. (2008). An experimental study of graph classification using prototype selection. In: Proceedings of the 19th International Conference on Pattern Recognition, 8-11 December 2008, Tampa, FL (pp. 1-4). New York: Institute of Electrical and Electronics Engineers IEEE 10.1109/ICPR.2008.4761811
Bunke, Horst; Riesen, Kaspar (2008). Recent developments in graph classification and clustering using graph embedding kernels. In: Juan-Ciscar, Alfonso; Sanchez-Albaladejo, Gemma (eds.) Proceedings of the 8th International Workshop on Pattern Recognition in Information Systems, PRIS 2008 (pp. 3-13). Setúbal, Portugal: Institute for Systems and Technologies of Information (INSTICC)
Riesen, Kaspar; Bunke, Horst (2008). Non-linear transformations of vector space embedded graphs. In: Juan-Ciscar, Alfonso; Sanchez-Albaladejo, Gemma (eds.) Proceedings of the 8th International Workshop on Pattern Recognition in Information Systems, PRIS 2008 (pp. 173-183). Setúbal, Portugal: Institute for Systems and Technologies of Information (INSTICC)
Riesen, Kaspar; Fankhauser, Stefan; Bunke, Horst (2007). Speeding up Graph Edit Distance Computation with a Bipartite Heuristic. In: Frasconi, Paolo; Kersting, Kristian; Tsuda, Koji (eds.) MLG 2007. Mining and Learning with Graphs, Università degli Studi di Firenze, Aug. 1-3, 2007 (pp. 21-24). Verlag fehlt
Riesen, Kaspar; Bunke, Horst (2007). Structural classifier ensembles for vector space embedded graphs. In: IJCNN 2007. International Joint Conference on Neural Networks, Orlando, Florida, 12-17 Aug. 2007 (pp. 1500-1505). Verlag fehlt 10.1109/IJCNN.2007.4371180
Riesen, Kaspar; Kilchherr, Vivian; Bunke, Horst (2007). Reducing the dimensionality of vector space embeddings of graphs. In: Machine Learning and Data Mining in Pattern Recognition. 5th International Conference, MLDM 2007, Leipzig, Germany, July 18-20, 2007. Proceedings. Lecture Notes in Computer Science: Vol. 4571 (pp. 563-573). Heidelberg: Springer Verlag 10.1007/978-3-540-73499-4_42
Riesen, Kaspar; Bunke, Horst (2007). Classifier Ensembles for Vector Space Embedding of Graphs. In: Haindl, Michal; Kittler, Josef; Roli, Fabio (eds.) Multiple Classifier Systems. Lecture Notes in Computer Science: Vol. 4472 (pp. 220-230). Heidelberg: Springer Verlag 10.1007/978-3-540-72523-7_23
Bunke, Horst; Riesen, Kaspar (2007). A family of novel graphs kernels for structural pattern recognition. In: Rueda, Luis; Mery, Dominco; Kittler, Josef (eds.) Progress in Pattern Recognition, Image Analysis and Applications. 12th Iberoamericann Congress on Pattern Recognition, CIARP 2007, Valparaiso, Chile, November 13-16, 2007. Proceedings. Lecture Notes in Computer Science: Vol. 4756 (pp. 20-31). Heidelberg: Springer Verlag 10.1007/978-3-540-76725-1_3
