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Kazumi Saito
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- affiliation: University of Shizuoka, Japan
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2020 – today
- 2023
- [j41]Yuki Yamagishi
, Kazumi Saito, Kazuro Hirahara
, Naonori Ueda:
Centrality measure and visualization technique for multiple-parent nodes of earthquakes based on correlation-metric. Appl. Netw. Sci. 8(1): 14 (2023) - [j40]Takayasu Fushimi, Kazumi Saito, Hiroshi Motoda:
Constructing outlier-free histograms with variable bin-width based on distance minimization. Intell. Data Anal. 27(1): 5-29 (2023) - 2022
- [j39]Takayasu Fushimi
, Kazumi Saito, Hiroshi Motoda:
Efficient computation of expected motif frequency in uncertain graphs by exploiting possible world marginalization and motif transition. Soc. Netw. Anal. Min. 12(1): 126 (2022) - 2021
- [j38]Yuki Yamagishi
, Kazumi Saito, Kazuro Hirahara, Naonori Ueda:
Spatio-temporal clustering of earthquakes based on distribution of magnitudes. Appl. Netw. Sci. 6(1): 71 (2021) - [j37]Kazumi Saito, Takayasu Fushimi, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Efficient computation of target-oriented link criticalness centrality in uncertain graphs. Intell. Data Anal. 25(5): 1323-1343 (2021) - [j36]Kazuo Aoyama
, Kazumi Saito, Tetsuo Ikeda:
CPI-model-based analysis of sparse k-means clustering algorithms. Int. J. Data Sci. Anal. 12(3): 229-248 (2021) - [j35]Takayasu Fushimi
, Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
General framework of opening and closing shops over a spatial network based on stochastic utility under competitive and time-bounded environment. Soc. Netw. Anal. Min. 11(1): 70 (2021) - [c136]Takayasu Fushimi, Kazumi Saito, Hiroshi Motoda:
Efficient analytical computation of expected frequency of motifs of small size by marginalization in uncertain network. ASONAM 2021: 1-8 - [c135]Yuki Yamagishi, Kazumi Saito, Kazuro Hirahara, Naonori Ueda:
Constructing Weighted Networks of Earthquakes with Multiple-parent Nodes Based on Correlation-Metric. COMPLEX NETWORKS 2021: 487-498 - [c134]Yuki Yamagishi
, Kazumi Saito, Kazuro Hirahara, Naonori Ueda:
Magnitude-Weighted Mean-Shift Clustering with Leave-One-Out Bandwidth Estimation. PRICAI (1) 2021: 347-358 - [i4]Kazuo Aoyama, Kazumi Saito:
Structured Inverted-File k-Means Clustering for High-Dimensional Sparse Data. CoRR abs/2103.16141 (2021) - 2020
- [j34]Takayasu Fushimi
, Seiya Okubo, Kazumi Saito:
Multiple perspective centrality measures based on facility location problem under inter-group competitive environment. Appl. Netw. Sci. 5(1): 80 (2020) - [j33]Kouzou Ohara
, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Resampling-based predictive simulation framework of stochastic diffusion model for identifying top-K influential nodes. Int. J. Data Sci. Anal. 9(2): 175-195 (2020) - [c133]Takayasu Fushimi, Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Opening and Closing Dynamics of Competing Shop Groups over Spatial Networks. ASONAM 2020: 393-400 - [c132]Takayasu Fushimi, Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Efficient Computing of PageRank Scores on Exact Expected Transition Matrix of Large Uncertain Graph. IEEE BigData 2020: 916-923 - [c131]Yuki Yamagishi
, Kazumi Saito, Kazuro Hirahara, Naonori Ueda:
Spatio-Temporal Clustering of Earthquakes Based on Average Magnitudes. COMPLEX NETWORKS (1) 2020: 627-637 - [c130]Kouzou Ohara, Takayasu Fushimi, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Maximizing Network Coverage Under the Presence of Time Constraint by Injecting Most Effective k-Links. DS 2020: 421-436 - [i3]Kazuo Aoyama, Kazumi Saito, Tetsuo Ikeda:
Inverted-File k-Means Clustering: Performance Analysis. CoRR abs/2002.09094 (2020)
2010 – 2019
- 2019
- [j32]Takayasu Fushimi
, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama:
Estimating node connectedness in spatial network under stochastic link disconnection based on efficient sampling. Appl. Netw. Sci. 4(1): 66:1-66:24 (2019) - [j31]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Critical Node Identification based on Articulation Point Detection for Uncertain Network. Int. J. Netw. Comput. 9(2): 201-216 (2019) - [c129]Takayasu Fushimi, Seiya Okubo, Kazumi Saito:
Facility Location Problem on Network Based on Group Centrality Measure Considering Cooperation and Competition. COMPLEX NETWORKS (1) 2019: 64-76 - [c128]Takayasu Fushimi, Kiyoto Iwasaki, Seiya Okubo, Kazumi Saito:
Construction of Histogram with Variable Bin-Width Based on Change Point Detection. DS 2019: 40-50 - [c127]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Resampling-Based Framework for Unbiased Estimator of Node Centrality over Large Complex Network. DS 2019: 428-442 - [c126]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Efficient Identification of Critical Links Based on Reachability Under the Presence of Time Constraint. PRICAI (2) 2019: 404-418 - 2018
- [j30]Takayasu Fushimi
, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama:
Improving approximate extraction of functional similar regions from large-scale spatial networks based on greedy selection of representative nodes of different areas. Appl. Netw. Sci. 3(1): 18:1-18:14 (2018) - [j29]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Which is more influential, "Who" or "When" for a user to rate in online review site? Intell. Data Anal. 22(3): 639-657 (2018) - [j28]Yuki Yamagishi
, Kazuo Aoyama, Kazumi Saito, Tetsuo Ikeda:
Pivot Generation Algorithm with a Complete Binary Tree for Efficient Exact Similarity Search. IEICE Trans. Inf. Syst. 101-D(1): 142-151 (2018) - [j27]Kazuo Aoyama, Kazumi Saito, Tetsuo Ikeda:
Accelerating a Lloyd-Type k-Means Clustering Algorithm with Summable Lower Bounds in a Lower-Dimensional Space. IEICE Trans. Inf. Syst. 101-D(11): 2773-2783 (2018) - [j26]Kazumi Saito
, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Accurate and efficient detection of critical links in network to minimize information loss. J. Intell. Inf. Syst. 51(2): 235-255 (2018) - [c125]Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama:
A New Group Centrality Measure for Maximizing the Connectedness of Network Under Uncertain Connectivity. COMPLEX NETWORKS (1) 2018: 3-14 - [c124]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Critical Node Identification Based on Articulation Point Detection for Network with Uncertain Connectivity. CANDAR 2018: 146-152 - [c123]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Critical Link Identification Based on Bridge Detection for Network with Uncertain Connectivity. ISMIS 2018: 89-99 - [c122]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Efficient Detection of Critical Links to Maintain Performance of Network with Uncertain Connectivity. PRICAI (1) 2018: 282-295 - 2017
- [j25]Yuki Yamagishi
, Kazuo Aoyama, Kazumi Saito, Tetsuo Ikeda:
Efficient Similarity Search with a Pivot-Based Complete Binary Tree. IEICE Trans. Inf. Syst. 100-D(10): 2526-2536 (2017) - [j24]Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama:
Clustering and Visualizing Functionally Similar Regions in Large-Scale Spatial Networks. J. Inf. Process. 25: 398-406 (2017) - [c121]Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama:
Fast Extraction Method of Functional Clusters from Large-Scale Spatial Networks Based on Transfer Learning. COMPLEX NETWORKS 2017: 1210-1222 - [c120]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Maximizing Network Performance Based on Group Centrality by Creating Most Effective k-Links. DSAA 2017: 561-570 - [c119]Kanji Matsutani, Masahito Kumano, Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Discovering Cooperative Structure Among Online Items for Attention Dynamics. ICDM Workshops 2017: 1033-1041 - [c118]Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama:
Accelerating Greedy K-Medoids Clustering Algorithm with L_1 Distance by Pivot Generation. ISMIS 2017: 87-96 - [c117]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
An Accurate and Efficient Method to Detect Critical Links to Maintain Information Flow in Network. ISMIS 2017: 116-126 - [c116]Yuki Yamagishi
, Kazumi Saito:
Visualizing Switching Regimes Based on Multinomial Distribution in Buzz Marketing Sites. ISMIS 2017: 385-395 - 2016
- [j23]Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Speeding-up node influence computation for huge social networks. Int. J. Data Sci. Anal. 1(1): 3-16 (2016) - [j22]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Super mediator - A new centrality measure of node importance for information diffusion over social network. Inf. Sci. 329: 985-1000 (2016) - [c115]Arief Maulana, Kazumi Saito, Tetsuo Ikeda, Hiroaki Yuze, Takayuki Watanabe, Seiya Okubo, Nobuaki Mutoh:
Characterizing Similarity Structure of Spatial Networks Based on Degree Mixing Patterns. AINA 2016: 9-16 - [c114]Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama:
Functional cluster extraction from large spatial networks. ASONAM 2016: 57-62 - [c113]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Accelerating Computation of Distance Based Centrality Measures for Spatial Networks. DS 2016: 376-391 - [c112]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Detecting Critical Links in Complex Network to Maintain Information Flow/Reachability. PRICAI 2016: 419-432 - [c111]Yuki Yamagishi
, Kazumi Saito, Tetsuo Ikeda:
Modeling of Travel Behavior Processes from Social Media. PRICAI 2016: 626-637 - [c110]Takashi Hattori, Kazuo Aoyama, Kazumi Saito, Tetsuo Ikeda, Eri Kobayashi:
Pivot-based k-means Algorithm for Numerous-class Data Sets. SDM 2016: 333-341 - [c109]Takayasu Fushimi, Tetsuji Satoh, Kazumi Saito, Kazuhiro Kazama, Noriko Kando
:
Content Centrality Measure for Networks: Introducing Distance-Based Decay Weights. SocInfo (2) 2016: 40-54 - 2015
- [j21]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Change point detection for burst analysis from an observed information diffusion sequence of tweets. J. Intell. Inf. Syst. 44(2): 243-269 (2015) - [c108]Kanji Matsutani, Masahito Kumano, Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Combining activity-evaluation information with NMF for trust-link prediction in social media. IEEE BigData 2015: 2263-2272 - [c107]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Change Point Detection for Information Diffusion Tree. Discovery Science 2015: 161-169 - [c106]Takayasu Fushimi, Tetsuji Satoh, Kazumi Saito, Kazuhiro Kazama:
Comparison of influence measures on structural changes focused on node functions. iiWAS 2015: 16:1-16:10 - [c105]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Resampling-Based Gap Analysis for Detecting Nodes with High Centrality on Large Social Network. PAKDD (1) 2015: 135-147 - [c104]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Efficient Learning of User Conformity on Review Score. SBP 2015: 182-192 - 2014
- [c103]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Resampling-Based Framework for Estimating Node Centrality of Large Social Network. Discovery Science 2014: 228-239 - [c102]Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Efficient analysis of node influence based on SIR model over huge complex networks. DSAA 2014: 216-222 - [c101]Takayasu Fushimi, Kazumi Saito, Kazuhiro Kazama:
Estimating Network Structure from Anonymous Ego-centric Information. PKAW 2014: 236-245 - [c100]Keito Hatta, Masahito Kumano, Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Analyzing Mediator-Activity Effects for Trust-Network Evolution in Social Media. PRICAI 2014: 297-308 - [c99]Eri Kobayashi, Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda:
Similarity Search by Generating Pivots Based on Manhattan Distance. PRICAI 2014: 435-446 - [c98]Shoko Kato, Kazumi Saito, Kazuhiro Kazama, Tetsuji Satoh:
MDSR: An Eigenvector Approach to Core Analysis of Multiple Directed Graphs. PRICAI 2014: 447-458 - [c97]Yuki Yamagishi, Seiya Okubo, Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
A Method to Divide Stream Data of Scores over Review Sites. PRICAI 2014: 913-919 - [c96]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
A New Approach for Item Ranking Based on Review Scores Reflecting Temporal Trust Factor. SBP 2014: 161-168 - 2013
- [j20]Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Learning to predict opinion share and detect anti-majority opinionists in social networks. J. Intell. Inf. Syst. 41(1): 5-37 (2013) - [j19]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Detecting changes in information diffusion patterns over social networks. ACM Trans. Intell. Syst. Technol. 4(3): 55:1-55:23 (2013) - [c95]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Predictive Simulation Framework of Stochastic Diffusion Model for Identifying Top-K Influential Nodes. ACML 2013: 149-164 - [c94]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Detecting changes in content and posting time distributions in social media. ASONAM 2013: 572-578 - [c93]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Identifying Super-Mediators of Information Diffusion in Social Networks. Discovery Science 2013: 170-184 - [c92]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Which Targets to Contact First to Maximize Influence over Social Network. SBP 2013: 359-367 - 2012
- [j18]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Efficient discovery of influential nodes for SIS models in social networks. Knowl. Inf. Syst. 30(3): 613-635 (2012) - [c91]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Burst Detection in a Sequence of Tweets Based on Information Diffusion Model. Discovery Science 2012: 239-253 - [c90]Shoko Kato, Akihiro Koide, Takayasu Fushimi, Kazumi Saito, Hiroshi Motoda:
Network Analysis of Three Twitter Functions: Favorite, Follow and Mention. PKAW 2012: 298-312 - [c89]Takayasu Fushimi, Kazumi Saito, Kazuhiro Kazama:
Extracting Communities in Networks Based on Functional Properties of Nodes. PKAW 2012: 328-334 - [c88]Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Opinion Formation by Voter Model with Temporal Decay Dynamics. ECML/PKDD (2) 2012: 565-580 - [c87]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Effect of In/Out-Degree Correlation on Influence Degree of Two Contrasting Information Diffusion Models. SBP 2012: 131-138 - [c86]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Graph embedding on spheres and its application to visualization of information diffusion data. WWW (Companion Volume) 2012: 1137-1144 - [i2]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Learning Asynchronous-Time Information Diffusion Models and its Application to Behavioral Data Analysis over Social Networks. CoRR abs/1204.4528 (2012) - 2011
- [j17]Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Learning information diffusion model in a social network for predicting influence of nodes. Intell. Data Anal. 15(4): 633-652 (2011) - [c85]Takayasu Fushimi, Yamato Kubota, Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Speeding Up Bipartite Graph Visualization Method. Australasian Conference on Artificial Intelligence 2011: 697-706 - [c84]Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Detecting Anti-majority Opinionists Using Value-Weighted Mixture Voter Model. Discovery Science 2011: 150-164 - [c83]Kazumi Saito, Kouzou Ohara, Yuki Yamagishi
, Masahiro Kimura, Hiroshi Motoda:
Learning Diffusion Probability Based on Node Attributes in Social Networks. ISMIS 2011: 153-162 - [c82]Kazuo Aoyama, Kazumi Saito, Hiroshi Sawada, Naonori Ueda:
Fast approximate similarity search based on degree-reduced neighborhood graphs. KDD 2011: 1055-1063 - [c81]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Detecting Changes in Opinion Value Distribution for Voter Model. SBP 2011: 89-96 - [c80]Yuki Yamagishi, Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Learning Attribute-weighted Voter Model over Social Networks. ACML 2011: 263-280 - [c79]Akihiro Koide, Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Estimating Diffusion Probability Changes for AsIC-SIS Model. ACML 2011: 297-313 - [i1]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Efficient Detection of Hot Span in Information Diffusion from Observation. CoRR abs/1110.2659 (2011) - 2010
- [j16]Masahiro Kimura, Kazumi Saito, Ryohei Nakano, Hiroshi Motoda:
Extracting influential nodes on a social network for information diffusion. Data Min. Knowl. Discov. 20(1): 70-97 (2010) - [c78]Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Learning to Predict Opinion Share in Social Networks. AAAI 2010: 1364-1370 - [c77]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Discovery of Super-Mediators of Information Diffusion in Social Networks. Discovery Science 2010: 144-158 - [c76]Yusuke Tanahashi, Ryohei Nakano, Kazumi Saito:
Nominally Conditioned Linear Regression. ICANN (3) 2010: 290-293 - [c75]Kazuo Aoyama, Shinji Watanabe
, Hiroshi Sawada, Yasuhiro Minami, Naonori Ueda, Kazumi Saito:
Fast similarity search on a large speech data set with neighborhood graph indexing. ICASSP 2010: 5358-5361 - [c74]Takayasu Fushimi, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda, Kouzou Ohara:
Finding Relation between PageRank and Voter Model. PKAW 2010: 208-222 - [c73]Yuya Yoshikawa, Kazumi Saito, Hiroshi Motoda, Kouzou Ohara, Masahiro Kimura:
Acquiring Expected Influence Curve from Single Diffusion Sequence. PKAW 2010: 273-287 - [c72]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Selecting Information Diffusion Models over Social Networks for Behavioral Analysis. ECML/PKDD (3) 2010: 180-195 - [c71]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Efficient Estimation of Cumulative Influence for Multiple Activation Information Diffusion Model with Continuous Time Delay. PRICAI 2010: 244-255 - [c70]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Behavioral Analyses of Information Diffusion Models by Observed Data of Social Network. SBP 2010: 149-158 - [c69]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Generative Models of Information Diffusion with Asynchronous Timedelay. ACML 2010: 193-208
2000 – 2009
- 2009
- [j15]Masahiro Kimura, Kazumi Saito, Hiroshi Motoda:
Blocking links to minimize contamination spread in a social network. ACM Trans. Knowl. Discov. Data 3(2): 9:1-9:23 (2009) - [c68]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Learning Continuous-Time Information Diffusion Model for Social Behavioral Data Analysis. ACML 2009: 322-337 - [c67]Kazuo Aoyama, Kazumi Saito, Takeshi Yamada, Naonori Ueda:
Fast Similarity Search in Small-World Networks. CompleNet 2009: 185-196 - [c66]Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Discovering Influential Nodes for SIS Models in Social Networks. Discovery Science 2009: 302-316 - [c65]Masahiro Kimura, Kazumi Saito, Hiroshi Motoda:
Efficient Estimation of Influence Functions for SIS Model on Social Networks. IJCAI 2009: 2046-2051 - [c64]Ken-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 - [p2]Kazumi Saito, Takeshi Yamada, Kazuhiro Kazama:
The k-Dense Method to Extract Communities from Complex Networks. Mining Complex Data 2009: 243-257 - 2008
- [j14]Kazumi Saito, Takeshi Yamada, Kazuhiro Kazama:
Extracting Communities from Complex Networks by the k-Dense Method. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 91-A(11): 3304-3311 (2008) - [j13]Akinori 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) - [j12]Tomoharu Iwata, Kazumi Saito, Takeshi Yamada:
Recommendation Method for Improving Customer Lifetime Value. IEEE Trans. Knowl. Data Eng. 20(9): 1254-1263 (2008) - [c63]Ken-ichi Fukui, Kazumi Saito, Masahiro Kimura, Masayuki Numao:
Sequence-based SOM: Visualizing transition of dynamic clusters. CIT 2008: 47-52 - [c62]Masahiro Kimura, Kazumi Saito, Hiroshi Motoda:
Minimizing the Spread of Contamination by Blocking Links in a Network. AAAI 2008: 1175-1180 - [c61]Masahiro Kimura, Kazumasa Yamakawa, Kazumi Saito, Hiroshi Motoda:
Community analysis of influential nodes for information diffusion on a social network. IJCNN 2008: 1358-1363 - [c60]Kazumi 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 - [c59]Kazumi Saito, Ryohei Nakano, Masahiro Kimura:
Prediction of Information Diffusion Probabilities for Independent Cascade Model. KES (3) 2008: 67-75 - [c58]Takayasu Fushimi, Takashi Kawazoe, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
What Does an Information Diffusion Model Tell about Social Network Structure?. PKAW 2008: 122-136 - [c57]Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Effective Visualization of Information Diffusion Process over Complex Networks. ECML/PKDD (2) 2008: 326-341 - [c56]Masahiro Kimura, Kazumi Saito, Hiroshi Motoda:
Solving the Contamination Minimization Problem on Networks for the Linear Threshold Model. PRICAI 2008: 977-984 - 2007
- [j11]Akinori Fujino, Naonori Ueda, Kazumi Saito:
A hybrid generative/discriminative approach to text classification with additional information. Inf. Process. Manag. 43(2): 379-392 (2007) - [j10]Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean Stromsten, Thomas L. Griffiths, Joshua B. Tenenbaum:
Parametric Embedding for Class Visualization. Neural Comput. 19(9): 2536-2556 (2007) - [j9]Kazumi Saito, Ryohei Nakano:
Bidirectional clustering of weights for neural networks with common weights. Syst. Comput. Jpn. 38(10): 46-57 (2007) - [c55]Masahiro Kimura, Kazumi Saito, Ryohei Nakano:
Extracting Influential Nodes for Information Diffusion on a Social Network. AAAI 2007: 1371-1376 - [c54]Ken-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 - [c53]Akinori Fujino, Naonori Ueda, Kazumi Saito:
Semi-Supervised Learning for Multi-Component Data Classification. IJCAI 2007: 2754-2759 - [c52]Pablo A. Estévez
, Pablo A. Vera, Kazumi Saito:
Selecting the Most Influential Nodes in Social Networks. IJCNN 2007: 2397-2402 - [c51]Ken-ichi Fukui, Kazumi Saito, Masahiro Kimura, Masayuki Numao:
Interpretable Likelihood for Vector Representable Topic. KES (3) 2007: 202-209 - [c50]Manabu Kimura, Kazumi Saito, Naonori Ueda:
Pivot Learning for Efficient Similarity Search. KES (3) 2007: 227-234 - [c49]Kazumi Saito, Ryohei Nakano, Masahiro Kimura:
Prediction of Link Attachments by Estimating Probabilities of Information Propagation. KES (3) 2007: 235-242 - [c48]Tomoharu Iwata, Kazumi Saito, Takeshi Yamada:
Modeling user behavior in recommender systems based on maximum entropy. WWW 2007: 1281-1282 - [p1]Kazumi Saito, Pat Langley:
Quantitative Revision of Scientific Models. Computational Discovery of Scientific Knowledge 2007: 120-137 - 2006
- [j8]Naonori Ueda, Kazumi Saito:
Parametric mixture model for multitopic text. Syst. Comput. Jpn. 37(2): 56-66 (2006) - [c47]Tomoharu Iwata, Kazumi Saito, Naonori Ueda:
Visual nonlinear discriminant analysis for classifier design. ESANN 2006: 283-288 - [c46]Kazumi Saito, Takeshi Yamada:
Extracting Communities from Complex Networks by the k-dense Method. ICDM Workshops 2006: 300-304 - [c45]Tomoharu Iwata, Kazumi Saito, Takeshi Yamada:
Recommendation method for extending subscription periods. KDD 2006: 574-579 - [c44]Ken-ichi Fukui, Kazumi Saito, Masahiro Kimura, Masayuki Numao:
Visualization Architecture Based on SOM for Two-Class Sequential Data. KES (2) 2006: 929-936 - [c43]Masahiro Kimura, Kazumi Saito:
Approximate Solutions for the Influence Maximization Problem in a Social Network. KES (2) 2006: 937-944 - [c42]Kazumi Saito, Ryohei Nakano:
Improving Convergence Performance of PageRank Computation Based on Step-Length Calculation Approach. KES (2) 2006: 945-952 - [c41]Yusuke 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 - [c40]Masahiro Kimura, Kazumi Saito:
Tractable Models for Information Diffusion in Social Networks. PKDD 2006: 259-271 - 2005
- [j7]Tomoharu Iwata, Kazumi Saito:
Visualization of Anomalies Using Mixture Models. J. Intell. Manuf. 16(6): 635-643 (2005) - [j6]Pablo 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) - [c39]Akinori Fujino, Naonori Ueda, Kazumi Saito:
A Hybrid Generative/Discriminative Approach to Semi-Supervised Classifier Design. AAAI 2005: 764-769 - [c38]Akinori Fujino, Naonori Ueda, Kazumi Saito:
A Classifier Design Based on Combining Multiple Components by Maximum Entropy Principle. AIRS 2005: 423-438 - [c37]Yusuke Tanahashi, Kazumi Saito, Ryohei Nakano:
Model Selection and Weight Sharing of Multi-layer Perceptrons. KES (4) 2005: 716-722 - [c36]Masahiro Kimura, Kazumi Saito, Kazuhiro Kazama, Shin-ya Sato:
Detecting Search Engine Spam from a Trackback Network in Blogspace. KES (4) 2005: 723-729 - [c35]Ken-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 - 2004
- [j5]Masahiro Kimura, Kazumi Saito, Naonori Ueda:
Modeling of growing networks with directional attachment and communities. Neural Networks 17(7): 975-988 (2004) - [j4]Masahiro Kimura, Kazumi Saito, Naonori Ueda:
Modeling network growth with directional attachment and communities. Syst. Comput. Jpn. 35(8): 1-11 (2004) - [c34]Yusuke Tanahashi, Kazumi Saito, Ryohei Nakano:
Piecewise Multivariate Polynomials Using a Four-Layer Perceptron. KES 2004: 602-608 - [c33]Yuji Kaneda, Naonori Ueda, Kazumi Saito:
Extended Parametric Mixture Model for Robust Multi-labeled Text Categorization. KES 2004: 616-623 - [c32]Tomoharu Iwata, Kazumi Saito:
Visualisation of Anomaly Using Mixture Model. KES 2004: 624-631 - [c31]Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean Stromsten, Thomas L. Griffiths, Joshua B. Tenenbaum:
Parametric Embedding for Class Visualization. NIPS 2004: 617-624 - [c30]Yuji Kaneda, Naonori Ueda, Kazumi Saito:
Document Clustering at NTCIR-4 Workshop: Limiting Search Space of the K-Means Method Using Word Occurrence. NTCIR 2004 - 2003
- [c29]Dileep George, Kazumi Saito, Pat Langley, Stephen D. Bay, Kevin R. Arrigo:
Discovering Ecosystem Models from Time-Series Data. Discovery Science 2003: 141-152 - [c28]Kazumi Saito, Dileep George, Stephen D. Bay, Jeff Shrager:
Inducing Biological Models from Temporal Gene Expression Data. Discovery Science 2003: 468-469 - [c27]Masahiro Kimura, Kazumi Saito, Naonori Ueda:
Modeling of growing networks with directional attachment and communities. ESANN 2003: 15-20 - [c26]Pat Langley, Dileep George, Stephen D. Bay, Kazumi Saito:
Robust Induction of Process Models from Time-Series Data. ICML 2003: 432-439 - [c25]Takeshi Yamada, Kazumi Saito, Naonori Ueda:
Cross-Entropy Directed Embedding of Network Data. ICML 2003: 832-839 - 2002
- [j3]Kazumi Saito, Ryohei Nakano:
Extracting regression rules from neural networks. Neural Networks 15(10): 1279-1288 (2002) - [c24]Kazumi Saito, Stephen D. Bay, Pat Langley:
Revising Qualitative Models of Gene Regulation. Discovery Science 2002: 59-70 - [c23]Kazumi Saito, Ryohei Nakano:
Structuring Neural Networks through Bidirectional Clustering of Weights. Discovery Science 2002: 206-219 - [c22]Ryohei Nakano, Kazumi Saito:
Discovering Polynomials to Fit Multivariate Data Having Numeric and Nominal Variables. Progress in Discovery Science 2002: 482-493 - [c21]Naonori Ueda, Kazumi Saito:
Single-shot detection of multiple categories of text using parametric mixture models. KDD 2002: 626-631 - [c20]Naonori Ueda, Kazumi Saito:
Parametric Mixture Models for Multi-Labeled Text. NIPS 2002: 721-728 - [c19]Masahiro Kimura, Kazumi Saito, Naonori Ueda:
Modeling of growing networks with communities. NNSP 2002: 189-198 - [c18]Kazumi Saito, Pat Langley:
Discovering Empirical Laws of Web Dynamics. SAINT 2002: 168-175 - 2001
- [c17]Kazumi Saito, Pat Langley, Trond Grenager, Christopher Potter, Alicia Torregrosa, Steven A. Klooster:
Computational Revision of Quantitative Scientific Models. Discovery Science 2001: 336-349 - [c16]Ryohei Nakano, Kazumi Saito:
Finding Polynomials to Fit Multivariate Data Having Numeric and Nominal Variables. IDA 2001: 258-267 - 2000
- [j2]Kazumi Saito, Ryohei Nakano:
Second-Order Learning Algorithm with Squared Penalty Term. Neural Comput. 12(3): 709-729 (2000) - [c15]Kazumi Saito, Naonori Ueda, Shigeru Katagiri, Yutaka Fukai, Hiroshi Fujimaru, Masayuki Fujinawa:
Law discovery from financial data using neural networks. CIFEr 2000: 209-212 - [c14]Kazumi Saito, Ryohei Nakano:
Discovery of Nominally Conditioned Polynomials Using Neural Networks, Vector Quantizers and Decision Trees. Discovery Science 2000: 325-329 - [c13]Kazumi Saito, Ryohei Nakano:
Discovery of Relevant Weights by Minimizing Cross-Validation Error. PAKDD 2000: 372-375
1990 – 1999
- 1999
- [c12]Ryohei Nakano, Kazumi Saito:
Discovery of a Set of Nominally Conditioned Polynomials. Discovery Science 1999: 287-298 - 1998
- [c11]Ryohei Nakano, Kazumi Saito:
Computational Characteristics of Law Discovery Using Neural Networks. Discovery Science 1998: 342-351 - 1997
- [j1]Kazumi Saito, Ryohei Nakano:
Partial BFGS Update and Efficient Step-Length Calculation for Three-Layer Neural Networks. Neural Comput. 9(1): 123-141 (1997) - [c10]Kazumi Saito, Ryohei Nakano:
MDL regularizer: a new regularizer based on the MDL principle. ICNN 1997: 1833-1838 - [c9]Kazumi Saito, Ryohei Nakano:
Numeric Law Discovery Using Neural Networks. ICONIP (2) 1997: 843-846 - [c8]Kazumi Saito, Ryohei Nakano:
Law Discovery using Neural Networks. IJCAI 1997: 1078-1083 - 1996
- [c7]Kazumi Saito, Ryohei Nakano:
A constructive learning algorithm for an HME. ICNN 1996: 1268-1273 - [c6]Kazumi Saito, Ryohei Nakano:
Second-order Learning Algorithm with Squared Penalty Term. NIPS 1996: 627-633 - 1995
- [c5]Ryohei Nakano, Naonori Ueda, Kazumi Saito, Takeshi Yamada:
Parrot-like speaking using optimal vector quantization. ICNN 1995: 2871-2875 - [c4]Kazumi Saito, Ryohei Nakano:
A Connectionist Approach to Numeric Law Discorvery. Machine Intelligence 15 1995: 315-327 - 1994
- [c3]Kazumi Saito, Ryohei Nakano:
Adaptive Concept Learning Algorithm. IFIP Congress (1) 1994: 294-299 - 1993
- [c2]Kazumi Saito, Ryohei Nakano:
A concept learning algorithm with adaptive search. Machine Intelligence 14 1993: 353-
1980 – 1989
- 1988
- [c1]Kazumi Saito, Ryohei Nakano:
Medical diagnostic expert system based on PDP model. ICNN 1988: 255-262
Coauthor Index
![](https://dblp1.uni-trier.de/img/cog.dark.24x24.png)
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