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Kazumi Saito Vis

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*2009
73EEKazumi Saito, Masahiro Kimura, Hiroshi Motoda: Discovering Influential Nodes for SIS Models in Social Networks. Discovery Science 2009: 302-316
72EEMasahiro Kimura, Kazumi Saito, Hiroshi Motoda: Efficient Estimation of Influence Functions for SIS Model on Social Networks. IJCAI 2009: 2046-2051
71EEKen-ichi Fukui, Kazuhisa Sato, Junichiro Mizusaki, Kazumi Saito, Masahiro Kimura, Masayuki Numao: Growth Analysis of Neighbor Network for Evaluation of Damage Progress. PAKDD 2009: 933-940
70EEKazumi Saito, Takeshi Yamada, Kazuhiro Kazama: The k-Dense Method to Extract Communities from Complex Networks. Mining Complex Data 2009: 243-257
69EEMasahiro Kimura, Kazumi Saito, Hiroshi Motoda: Blocking links to minimize contamination spread in a social network. TKDD 3(2): (2009)
2008
68 Masahiro Kimura, Kazumi Saito, Hiroshi Motoda: Minimizing the Spread of Contamination by Blocking Links in a Network. AAAI 2008: 1175-1180
67EEKazumi Saito, Masahiro Kimura, Hiroshi Motoda: Effective Visualization of Information Diffusion Process over Complex Networks. ECML/PKDD (2) 2008: 326-341
66EEMasahiro Kimura, Kazumasa Yamakawa, Kazumi Saito, Hiroshi Motoda: Community analysis of influential nodes for information diffusion on a social network. IJCNN 2008: 1358-1363
65EEKazumi Saito, Nobuaki Mutoh, Tetsuo Ikeda, Toshinao Goda, Kazuki Mochizuki: Improving Search Efficiency of Incremental Variable Selection by Using Second-Order Optimal Criterion. KES (3) 2008: 41-49
64EEKazumi Saito, Ryohei Nakano, Masahiro Kimura: Prediction of Information Diffusion Probabilities for Independent Cascade Model. KES (3) 2008: 67-75
63EETakayasu Fushimi, Takashi Kawazoe, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda: What Does an Information Diffusion Model Tell about Social Network Structure?. PKAW 2008: 122-136
62EEMasahiro Kimura, Kazumi Saito, Hiroshi Motoda: Solving the Contamination Minimization Problem on Networks for the Linear Threshold Model. PRICAI 2008: 977-984
61EETomoharu Iwata, Kazumi Saito, Takeshi Yamada: Recommendation Method for Improving Customer Lifetime Value. IEEE Trans. Knowl. Data Eng. 20(9): 1254-1263 (2008)
60EEAkinori Fujino, Naonori Ueda, Kazumi Saito: Semisupervised Learning for a Hybrid Generative/Discriminative Classifier based on the Maximum Entropy Principle. IEEE Trans. Pattern Anal. Mach. Intell. 30(3): 424-437 (2008)
59EEKazumi Saito, Takeshi Yamada, Kazuhiro Kazama: Extracting Communities from Complex Networks by the k-Dense Method. IEICE Transactions 91-A(11): 3304-3311 (2008)
2007
58 Masahiro Kimura, Kazumi Saito, Ryohei Nakano: Extracting Influential Nodes for Information Diffusion on a Social Network. AAAI 2007: 1371-1376
57EEKazumi Saito, Pat Langley: Quantitative Revision of Scientific Models. Computational Discovery of Scientific Knowledge 2007: 120-137
56EEKen-ichi Fukui, Kazuhisa Sato, Junichiro Mizusaki, Kazumi Saito, Masayuki Numao: Combining Burst Extraction Method and Sequence-Based SOM for Evaluation of Fracture Dynamics in Solid Oxide Fuel Cell. ICTAI (2) 2007: 193-196
55EEAkinori Fujino, Naonori Ueda, Kazumi Saito: Semi-Supervised Learning for Multi-Component Data Classification. IJCAI 2007: 2754-2759
54EEPablo A. Estévez, Pablo A. Vera, Kazumi Saito: Selecting the Most Influential Nodes in Social Networks. IJCNN 2007: 2397-2402
53EEKen-ichi Fukui, Kazumi Saito, Masahiro Kimura, Masayuki Numao: Interpretable Likelihood for Vector Representable Topic. KES (3) 2007: 202-209
52EEManabu Kimura, Kazumi Saito, Naonori Ueda: Pivot Learning for Efficient Similarity Search. KES (3) 2007: 227-234
51EEKazumi Saito, Ryohei Nakano, Masahiro Kimura: Prediction of Link Attachments by Estimating Probabilities of Information Propagation. KES (3) 2007: 235-242
50EETomoharu Iwata, Kazumi Saito, Takeshi Yamada: Modeling user behavior in recommender systems based on maximum entropy. WWW 2007: 1281-1282
49EEAkinori Fujino, Naonori Ueda, Kazumi Saito: A hybrid generative/discriminative approach to text classification with additional information. Inf. Process. Manage. 43(2): 379-392 (2007)
48EETomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean Stromsten, Thomas L. Griffiths, Joshua B. Tenenbaum: Parametric Embedding for Class Visualization. Neural Computation 19(9): 2536-2556 (2007)
47EEKazumi Saito, Ryohei Nakano: Bidirectional clustering of weights for neural networks with common weights. Systems and Computers in Japan 38(10): 46-57 (2007)
2006
46EETomoharu Iwata, Kazumi Saito, Naonori Ueda: Visual nonlinear discriminant analysis for classifier design. ESANN 2006: 283-288
45EEKazumi Saito, Takeshi Yamada: Extracting Communities from Complex Networks by the k-dense Method. ICDM Workshops 2006: 300-304
44EETomoharu Iwata, Kazumi Saito, Takeshi Yamada: Recommendation method for extending subscription periods. KDD 2006: 574-579
43EEKen-ichi Fukui, Kazumi Saito, Masahiro Kimura, Masayuki Numao: Visualization Architecture Based on SOM for Two-Class Sequential Data. KES (2) 2006: 929-936
42EEMasahiro Kimura, Kazumi Saito: Approximate Solutions for the Influence Maximization Problem in a Social Network. KES (2) 2006: 937-944
41EEKazumi Saito, Ryohei Nakano: Improving Convergence Performance of PageRank Computation Based on Step-Length Calculation Approach. KES (2) 2006: 945-952
40EEYusuke Tanahashi, Kazumi Saito, Daisuke Kitakoshi, Ryohei Nakano: Finding Nominally Conditioned Multivariate Polynomials Using a Four-Layer Perceptron Having Shared Weights. KES (2) 2006: 969-976
39EEMasahiro Kimura, Kazumi Saito: Tractable Models for Information Diffusion in Social Networks. PKDD 2006: 259-271
38EENaonori Ueda, Kazumi Saito: Parametric mixture model for multitopic text. Systems and Computers in Japan 37(2): 56-66 (2006)
2005
37 Akinori Fujino, Naonori Ueda, Kazumi Saito: A Hybrid Generative/Discriminative Approach to Semi-Supervised Classifier Design. AAAI 2005: 764-769
36EEAkinori Fujino, Naonori Ueda, Kazumi Saito: A Classifier Design Based on Combining Multiple Components by Maximum Entropy Principle. AIRS 2005: 423-438
35EEYusuke Tanahashi, Kazumi Saito, Ryohei Nakano: Model Selection and Weight Sharing of Multi-layer Perceptrons. KES (4) 2005: 716-722
34EEMasahiro Kimura, Kazumi Saito, Kazuhiro Kazama, Shin-ya Sato: Detecting Search Engine Spam from a Trackback Network in Blogspace. KES (4) 2005: 723-729
33EEKen-ichi Fukui, Kazumi Saito, Masahiro Kimura, Masayuki Numao: Visualizing Dynamics of the Hot Topics Using Sequence-Based Self-organizing Maps. KES (4) 2005: 745-751
32EEPablo A. Estévez, Cristián J. Figueroa, Kazumi Saito: Cross-entropy embedding of high-dimensional data using the neural gas model. Neural Networks 18(5-6): 727-737 (2005)
2004
31EEYusuke Tanahashi, Kazumi Saito, Ryohei Nakano: Piecewise Multivariate Polynomials Using a Four-Layer Perceptron. KES 2004: 602-608
30EEYuji Kaneda, Naonori Ueda, Kazumi Saito: Extended Parametric Mixture Model for Robust Multi-labeled Text Categorization. KES 2004: 616-623
29EETomoharu Iwata, Kazumi Saito: Visualisation of Anomaly Using Mixture Model. KES 2004: 624-631
28EETomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean Stromsten, Thomas L. Griffiths, Joshua B. Tenenbaum: Parametric Embedding for Class Visualization. NIPS 2004
27EEMasahiro Kimura, Kazumi Saito, Naonori Ueda: Modeling of growing networks with directional attachment and communities. Neural Networks 17(7): 975-988 (2004)
26EEMasahiro Kimura, Kazumi Saito, Naonori Ueda: Modeling network growth with directional attachment and communities. Systems and Computers in Japan 35(8): 1-11 (2004)
2003
25EEDileep George, Kazumi Saito, Pat Langley, Stephen D. Bay, Kevin R. Arrigo: Discovering Ecosystem Models from Time-Series Data. Discovery Science 2003: 141-152
24EEKazumi Saito, Dileep George, Stephen D. Bay, Jeff Shrager: Inducing Biological Models from Temporal Gene Expression Data. Discovery Science 2003: 468-469
23EEMasahiro Kimura, Kazumi Saito, Naonori Ueda: Modeling of growing networks with directional attachment and communities. ESANN 2003: 15-20
22 Pat Langley, Dileep George, Stephen D. Bay, Kazumi Saito: Robust Induction of Process Models from Time-Series Data. ICML 2003: 432-439
21 Takeshi Yamada, Kazumi Saito, Naonori Ueda: Cross-Entropy Directed Embedding of Network Data. ICML 2003: 832-839
2002
20EEKazumi Saito, Ryohei Nakano: Structuring Neural Networks through Bidirectional Clustering of Weights. Discovery Science 2002: 206-219
19EEKazumi Saito, Stephen D. Bay, Pat Langley: Revising Qualitative Models of Gene Regulation. Discovery Science 2002: 59-70
18EENaonori Ueda, Kazumi Saito: Single-shot detection of multiple categories of text using parametric mixture models. KDD 2002: 626-631
17EENaonori Ueda, Kazumi Saito: Parametric Mixture Models for Multi-Labeled Text. NIPS 2002: 721-728
16EERyohei Nakano, Kazumi Saito: Discovering Polynomials to Fit Multivariate Data Having Numeric and Nominal Variables. Progress in Discovery Science 2002: 482-493
15EEKazumi Saito, Pat Langley: Discovering Empirical Laws of Web Dynamics. SAINT 2002: 168-175
14EEKazumi Saito, Ryohei Nakano: Extracting regression rules from neural networks. Neural Networks 15(10): 1279-1288 (2002)
2001
13EEKazumi Saito, Pat Langley, Trond Grenager, Christopher Potter, Alicia Torregrosa, Steven A. Klooster: Computational Revision of Quantitative Scientific Models. Discovery Science 2001: 336-349
12EERyohei Nakano, Kazumi Saito: Finding Polynomials to Fit Multivariate Data Having Numeric and Nominal Variables. IDA 2001: 258-267
2000
11EEKazumi Saito, Ryohei Nakano: Discovery of Nominally Conditioned Polynomials Using Neural Networks, Vector Quantizers and Decision Trees. Discovery Science 2000: 325-329
10 Kazumi Saito, Ryohei Nakano: Discovery of Relevant Weights by Minimizing Cross-Validation Error. PAKDD 2000: 372-375
9 Kazumi Saito, Ryohei Nakano: Second-Order Learning Algorithm with Squared Penalty Term. Neural Computation 12(3): 709-729 (2000)
1999
8EERyohei Nakano, Kazumi Saito: Discovery of a Set of Nominally Conditioned Polynomials. Discovery Science 1999: 287-298
1998
7EERyohei Nakano, Kazumi Saito: Computational Characteristics of Law Discovery Using Neural Networks. Discovery Science 1998: 342-351
1997
6 Kazumi Saito, Ryohei Nakano: Law Discovery using Neural Networks. IJCAI 1997: 1078-1083
5EEKazumi Saito, Ryohei Nakano: Partial BFGS Update and Efficient Step-Length Calculation for Three-Layer Neural Networks. Neural Computation 9(1): 123-141 (1997)
1996
4EEKazumi Saito, Ryohei Nakano: Second-order Learning Algorithm with Squared Penalty Term. NIPS 1996: 627-633
1995
3 Kazumi Saito, Ryohei Nakano: A Connectionist Approach to Numeric Law Discorvery. Machine Intelligence 15 1995: 315-327
1994
2 Kazumi Saito, Ryohei Nakano: Adaptive Concept Learning Algorithm. IFIP Congress (1) 1994: 294-299
1993
1 Kazumi Saito, Ryohei Nakano: A concept learning algorithm with adaptive search. Machine Intelligence 14 1993: 353-

Coauthor Index

1Kevin R. Arrigo [25]
2Stephen D. Bay [19] [22] [24] [25]
3Pablo A. Estévez [32] [54]
4Cristián J. Figueroa [32]
5Akinori Fujino [36] [37] [49] [55] [60]
6Ken-ichi Fukui [33] [43] [53] [56] [71]
7Takayasu Fushimi [63]
8Dileep George [22] [24] [25]
9Toshinao Goda [65]
10Trond Grenager [13]
11Thomas L. Griffiths [28] [48]
12Tetsuo Ikeda [65]
13Tomoharu Iwata [28] [29] [44] [46] [48] [50] [61]
14Yuji Kaneda [30]
15Takashi Kawazoe [63]
16Kazuhiro Kazama [34] [59] [70]
17Manabu Kimura [52]
18Masahiro Kimura [23] [26] [27] [33] [34] [39] [42] [43] [51] [53] [58] [62] [63] [64] [66] [67] [68] [69] [71] [72] [73]
19Daisuke Kitakoshi [40]
20Steven A. Klooster [13]
21Pat Langley [13] [15] [19] [22] [25] [57]
22Junichiro Mizusaki [56] [71]
23Kazuki Mochizuki [65]
24Hiroshi Motoda [62] [63] [66] [67] [68] [69] [72] [73]
25Nobuaki Mutoh [65]
26Ryohei Nakano [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [14] [16] [20] [31] [35] [40] [41] [47] [51] [58] [64]
27Masayuki Numao [33] [43] [53] [56] [71]
28Christopher Potter [13]
29Kazuhisa Sato [56] [71]
30Shin-ya Sato [34]
31Jeff Shrager [24]
32Sean Stromsten [28] [48]
33Yusuke Tanahashi [31] [35] [40]
34Joshua B. Tenenbaum [28] [48]
35Alicia Torregrosa [13]
36Naonori Ueda [17] [18] [21] [23] [26] [27] [28] [30] [36] [37] [38] [46] [48] [49] [52] [55] [60]
37Pablo A. Vera [54]
38Takeshi Yamada [21] [44] [45] [50] [59] [61] [70]
39Kazumasa Yamakawa [66]

Colors in the list of coauthors

Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)