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Naonori Ueda: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Akinori Fujino, Naonori Ueda, Kazumi Saito
    A Hybrid Generative/Discriminative Approach to Semi-Supervised Classifier Design. [Citation Graph (0, 0)][DBLP]
    AAAI, 2005, pp:764-769 [Conf]
  2. Charles Kemp, Joshua B. Tenenbaum, Thomas L. Griffiths, Takeshi Yamada, Naonori Ueda
    Learning Systems of Concepts with an Infinite Relational Model. [Citation Graph (0, 0)][DBLP]
    AAAI, 2006, pp:- [Conf]
  3. Akinori Fujino, Naonori Ueda, Kazumi Saito
    A Classifier Design Based on Combining Multiple Components by Maximum Entropy Principle. [Citation Graph (0, 0)][DBLP]
    AIRS, 2005, pp:423-438 [Conf]
  4. Naonori Ueda, Kenji Mase
    Tracking Moving Contours Using Energy-Minimizing Elastic Contour Models. [Citation Graph (0, 0)][DBLP]
    ECCV, 1992, pp:453-457 [Conf]
  5. Masahiro Kimura, Kazumi Saito, Naonori Ueda
    Modeling of growing networks with directional attachment and communities. [Citation Graph (0, 0)][DBLP]
    ESANN, 2003, pp:15-20 [Conf]
  6. Tomoharu Iwata, Kazumi Saito, Naonori Ueda
    Visual nonlinear discriminant analysis for classifier design. [Citation Graph (0, 0)][DBLP]
    ESANN, 2006, pp:283-288 [Conf]
  7. Takeshi Yamada, Kazumi Saito, Naonori Ueda
    Cross-Entropy Directed Embedding of Network Data. [Citation Graph (0, 0)][DBLP]
    ICML, 2003, pp:832-839 [Conf]
  8. Akinori Fujino, Naonori Ueda, Kazumi Saito
    Semi-Supervised Learning for Multi-Component Data Classification. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2007, pp:2754-2759 [Conf]
  9. Naonori Ueda, Kazumi Saito
    Single-shot detection of multiple categories of text using parametric mixture models. [Citation Graph (0, 0)][DBLP]
    KDD, 2002, pp:626-631 [Conf]
  10. Yuji Kaneda, Naonori Ueda, Kazumi Saito
    Extended Parametric Mixture Model for Robust Multi-labeled Text Categorization. [Citation Graph (0, 0)][DBLP]
    KES, 2004, pp:616-623 [Conf]
  11. Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean Stromsten, Thomas L. Griffiths, Joshua B. Tenenbaum
    Parametric Embedding for Class Visualization. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  12. Naonori Ueda, Ryohei Nakano
    Deterministic Annealing Variant of the EM Algorithm. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:545-552 [Conf]
  13. Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton
    SMEM Algorithm for Mixture Models. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:599-605 [Conf]
  14. Naonori Ueda, Kazumi Saito
    Parametric Mixture Models for Multi-Labeled Text. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:721-728 [Conf]
  15. Shinji Watanabe, Yasuhiro Minami, Atsushi Nakamura, Naonori Ueda
    Application of Variational Bayesian Approach to Speech Recognition. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:1237-1244 [Conf]
  16. Masashi Inoue, Naonori Ueda
    Retrieving lightly annotated images using image similarities. [Citation Graph (0, 0)][DBLP]
    SAC, 2005, pp:1031-1037 [Conf]
  17. Shinji Watanabe, Yasuhiro Minami, Atsushi Nakamura, Naonori Ueda
    Selection of Shared-State Hidden Markov Model Structure Using Bayesian Criterion. [Citation Graph (0, 0)][DBLP]
    IEICE Transactions, 2005, v:88, n:1, pp:1-9 [Journal]
  18. Satoshi Suzuki, Naonori Ueda, Jack Sklansky
    Graph-Based Thinning for Binary Images. [Citation Graph (0, 0)][DBLP]
    IJPRAI, 1993, v:7, n:5, pp:1009-1030 [Journal]
  19. Naonori Ueda, Kenji Mase
    Tracking Moving Contours Using Energy-Minimizing Elastic Contour Models. [Citation Graph (0, 0)][DBLP]
    IJPRAI, 1995, v:9, n:3, pp:465-484 [Journal]
  20. Akinori Fujino, Naonori Ueda, Kazumi Saito
    A hybrid generative/discriminative approach to text classification with additional information. [Citation Graph (0, 0)][DBLP]
    Inf. Process. Manage., 2007, v:43, n:2, pp:379-392 [Journal]
  21. Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton
    SMEM Algorithm for Mixture Models. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:9, pp:2109-2128 [Journal]
  22. Masahiro Kimura, Kazumi Saito, Naonori Ueda
    Modeling of growing networks with directional attachment and communities. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2004, v:17, n:7, pp:975-988 [Journal]
  23. Naonori Ueda, Zoubin Ghahramani
    Bayesian model search for mixture models based on optimizing variational bounds. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2002, v:15, n:10, pp:1223-1241 [Journal]
  24. Naonori Ueda, Ryohei Nakano
    A new competitive learning approach based on an equidistortion principle for designing optimal vector quantizers. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1994, v:7, n:8, pp:1211-1227 [Journal]
  25. Naonori Ueda, Ryohei Nakano
    Deterministic annealing EM algorithm. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1998, v:11, n:2, pp:271-282 [Journal]
  26. Naonori Ueda
    Optimal Linear Combination of Neural Networks for Improving Classification Performance. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 2000, v:22, n:2, pp:207-215 [Journal]
  27. Naonori Ueda, Satoshi Suzuki
    Learning Visual Models from Shape Contours Using Multiscale Convex/Concave Structure Matching. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 1993, v:15, n:4, pp:337-352 [Journal]
  28. Masashi Inoue, Naonori Ueda
    Use of unlabeled time series data in hidden Markov models. [Citation Graph (0, 0)][DBLP]
    Systems and Computers in Japan, 2003, v:34, n:13, pp:1-12 [Journal]
  29. Masahiro Kimura, Kazumi Saito, Naonori Ueda
    Modeling network growth with directional attachment and communities. [Citation Graph (0, 0)][DBLP]
    Systems and Computers in Japan, 2004, v:35, n:8, pp:1-11 [Journal]
  30. Satoshi Suzuki, Naonori Ueda
    Adaptive clustering using modular learning architecture. [Citation Graph (0, 0)][DBLP]
    Systems and Computers in Japan, 2003, v:34, n:2, pp:70-80 [Journal]
  31. Naonori Ueda
    Optimal linear combination of neural network classifiers based on the minimum classification error criterion. [Citation Graph (0, 0)][DBLP]
    Systems and Computers in Japan, 2000, v:31, n:9, pp:39-48 [Journal]
  32. Naonori Ueda, Ryohei Nakano
    EM algorithm with split and merge operations for mixture models. [Citation Graph (0, 0)][DBLP]
    Systems and Computers in Japan, 2000, v:31, n:5, pp:1-11 [Journal]
  33. Naonori Ueda, Kazumi Saito
    Parametric mixture model for multitopic text. [Citation Graph (0, 0)][DBLP]
    Systems and Computers in Japan, 2006, v:37, n:2, pp:56-66 [Journal]
  34. Manabu Kimura, Kazumi Saito, Naonori Ueda
    Pivot Learning for Efficient Similarity Search. [Citation Graph (0, 0)][DBLP]
    KES (3), 2007, pp:227-234 [Conf]
  35. Shuhei Kuwata, Naonori Ueda
    One-shot Collaborative Filtering. [Citation Graph (0, 0)][DBLP]
    CIDM, 2007, pp:300-307 [Conf]

  36. Simultaneous clustering and tracking unknown number of objects. [Citation Graph (, )][DBLP]


  37. RAST: A Related Abstract Search Tool. [Citation Graph (, )][DBLP]


  38. Topic Tracking Model for Analyzing Consumer Purchase Behavior. [Citation Graph (, )][DBLP]


  39. 3D-SE Viewer: A Text Mining Tool based on Bipartite Graph Visualization. [Citation Graph (, )][DBLP]


  40. Extracting Keywords from Research Abstracts for the Neuroinformatics Platform Index Tree. [Citation Graph (, )][DBLP]


  41. Probabilistic latent semantic visualization: topic model for visualizing documents. [Citation Graph (, )][DBLP]


  42. Online multiscale dynamic topic models. [Citation Graph (, )][DBLP]


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