Naonori Ueda

2008
44	EE	Katsuhiko Ishiguro, Takeshi Yamada, Naonori Ueda: Simultaneous clustering and tracking unknown number of objects. CVPR 2008
43	EE	Tomoharu Iwata, Takeshi Yamada, Naonori Ueda: Probabilistic latent semantic visualization: topic model for visualizing documents. KDD 2008: 363-371
42	EE	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)
2007
41	EE	Shuhei Kuwata, Naonori Ueda: One-shot Collaborative Filtering. CIDM 2007: 300-307
40	EE	Akinori Fujino, Naonori Ueda, Kazumi Saito: Semi-Supervised Learning for Multi-Component Data Classification. IJCAI 2007: 2754-2759
39	EE	Shiro Usui, Antoine Naud, Naonori Ueda, Tatsuki Taniguchi: 3D-SE Viewer: A Text Mining Tool based on Bipartite Graph Visualization. IJCNN 2007: 1103-1108
38	EE	Manabu Kimura, Kazumi Saito, Naonori Ueda: Pivot Learning for Efficient Similarity Search. KES (3) 2007: 227-234
37	EE	Akinori Fujino, Naonori Ueda, Kazumi Saito: A hybrid generative/discriminative approach to text classification with additional information. Inf. Process. Manage. 43(2): 379-392 (2007)
36	EE	Tomoharu 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)
2006
35		Charles Kemp, Joshua B. Tenenbaum, Thomas L. Griffiths, Takeshi Yamada, Naonori Ueda: Learning Systems of Concepts with an Infinite Relational Model. AAAI 2006
34	EE	Tomoharu Iwata, Kazumi Saito, Naonori Ueda: Visual nonlinear discriminant analysis for classifier design. ESANN 2006: 283-288
33	EE	Shiro Usui, Paulito P. Palmes, Kazunori Nagata, Tatsuki Taniguchi, Naonori Ueda: Extracting Keywords from Research Abstracts for the Neuroinformatics Platform Index Tree. IJCNN 2006: 5045-5050
32	EE	Naonori Ueda, Kazumi Saito: Parametric mixture model for multitopic text. Systems and Computers in Japan 37(2): 56-66 (2006)
2005
31		Akinori Fujino, Naonori Ueda, Kazumi Saito: A Hybrid Generative/Discriminative Approach to Semi-Supervised Classifier Design. AAAI 2005: 764-769
30	EE	Akinori Fujino, Naonori Ueda, Kazumi Saito: A Classifier Design Based on Combining Multiple Components by Maximum Entropy Principle. AIRS 2005: 423-438
29	EE	Masashi Inoue, Naonori Ueda: Retrieving lightly annotated images using image similarities. SAC 2005: 1031-1037
28	EE	Shinji Watanabe, Yasuhiro Minami, Atsushi Nakamura, Naonori Ueda: Selection of Shared-State Hidden Markov Model Structure Using Bayesian Criterion. IEICE Transactions 88-D(1): 1-9 (2005)
2004
27	EE	Yuji Kaneda, Naonori Ueda, Kazumi Saito: Extended Parametric Mixture Model for Robust Multi-labeled Text Categorization. KES 2004: 616-623
26	EE	Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean Stromsten, Thomas L. Griffiths, Joshua B. Tenenbaum: Parametric Embedding for Class Visualization. NIPS 2004
25	EE	Masahiro Kimura, Kazumi Saito, Naonori Ueda: Modeling of growing networks with directional attachment and communities. Neural Networks 17(7): 975-988 (2004)
24	EE	Masahiro Kimura, Kazumi Saito, Naonori Ueda: Modeling network growth with directional attachment and communities. Systems and Computers in Japan 35(8): 1-11 (2004)
23	EE	Naonori Ueda, Masashi Inoue: Extended Tied-Mixture HMMs for Both Labeled and Unlabeled Time Series Data. VLSI Signal Processing 37(2-3): 189-197 (2004)
2003
22	EE	Masahiro Kimura, Kazumi Saito, Naonori Ueda: Modeling of growing networks with directional attachment and communities. ESANN 2003: 15-20
21		Takeshi Yamada, Kazumi Saito, Naonori Ueda: Cross-Entropy Directed Embedding of Network Data. ICML 2003: 832-839
20	EE	Masashi Inoue, Naonori Ueda: Exploitation of Unlabeled Sequences in Hidden Markov Models. IEEE Trans. Pattern Anal. Mach. Intell. 25(12): 1570-1581 (2003)
19	EE	Masashi Inoue, Naonori Ueda: Use of unlabeled time series data in hidden Markov models. Systems and Computers in Japan 34(13): 1-12 (2003)
18	EE	Satoshi Suzuki, Naonori Ueda: Adaptive clustering using modular learning architecture. Systems and Computers in Japan 34(2): 70-80 (2003)
2002
17	EE	Naonori Ueda, Kazumi Saito: Single-shot detection of multiple categories of text using parametric mixture models. KDD 2002: 626-631
16	EE	Shinji Watanabe, Yasuhiro Minami, Atsushi Nakamura, Naonori Ueda: Application of Variational Bayesian Approach to Speech Recognition. NIPS 2002: 1237-1244
15	EE	Naonori Ueda, Kazumi Saito: Parametric Mixture Models for Multi-Labeled Text. NIPS 2002: 721-728
14	EE	Naonori Ueda, Zoubin Ghahramani: Bayesian model search for mixture models based on optimizing variational bounds. Neural Networks 15(10): 1223-1241 (2002)
2000
13	EE	Naonori Ueda: Optimal Linear Combination of Neural Networks for Improving Classification Performance. IEEE Trans. Pattern Anal. Mach. Intell. 22(2): 207-215 (2000)
12		Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton: SMEM Algorithm for Mixture Models. Neural Computation 12(9): 2109-2128 (2000)
11	EE	Naonori Ueda, Ryohei Nakano: EM algorithm with split and merge operations for mixture models. Systems and Computers in Japan 31(5): 1-11 (2000)
10	EE	Naonori Ueda: Optimal linear combination of neural network classifiers based on the minimum classification error criterion. Systems and Computers in Japan 31(9): 39-48 (2000)
9	EE	Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton: Split and Merge EM Algorithm for Improving Gaussian Mixture Density Estimates. VLSI Signal Processing 26(1-2): 133-140 (2000)
1998
8	EE	Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton: SMEM Algorithm for Mixture Models. NIPS 1998: 599-605
7	EE	Naonori Ueda, Ryohei Nakano: Deterministic annealing EM algorithm. Neural Networks 11(2): 271-282 (1998)
1995
6		Naonori Ueda, Kenji Mase: Tracking Moving Contours Using Energy-Minimizing Elastic Contour Models. IJPRAI 9(3): 465-484 (1995)
1994
5	EE	Naonori Ueda, Ryohei Nakano: Deterministic Annealing Variant of the EM Algorithm. NIPS 1994: 545-552
4	EE	Naonori Ueda, Ryohei Nakano: A new competitive learning approach based on an equidistortion principle for designing optimal vector quantizers. Neural Networks 7(8): 1211-1227 (1994)
1993
3	EE	Naonori Ueda, Satoshi Suzuki: Learning Visual Models from Shape Contours Using Multiscale Convex/Concave Structure Matching. IEEE Trans. Pattern Anal. Mach. Intell. 15(4): 337-352 (1993)
2		Satoshi Suzuki, Naonori Ueda, Jack Sklansky: Graph-Based Thinning for Binary Images. IJPRAI 7(5): 1009-1030 (1993)
1992
1		Naonori Ueda, Kenji Mase: Tracking Moving Contours Using Energy-Minimizing Elastic Contour Models. ECCV 1992: 453-457

Coauthor Index

1	Akinori Fujino	[30] [31] [37] [40] [42]
2	Zoubin Ghahramani	[8] [9] [12] [14]
3	Thomas L. Griffiths	[26] [35] [36]
4	Geoffrey E. Hinton	[8] [9] [12]
5	Masashi Inoue	[19] [20] [23] [29]
6	Katsuhiko Ishiguro	[44]
7	Tomoharu Iwata	[26] [34] [36] [43]
8	Yuji Kaneda	[27]
9	Charles Kemp	[35]
10	Manabu Kimura	[38]
11	Masahiro Kimura	[22] [24] [25]
12	Shuhei Kuwata	[41]
13	Kenji Mase	[1] [6]
14	Yasuhiro Minami	[16] [28]
15	Kazunori Nagata	[33]
16	Atsushi Nakamura	[16] [28]
17	Ryohei Nakano	[4] [5] [7] [8] [9] [11] [12]
18	Antoine Naud	[39]
19	Paulito P. Palmes	[33]
20	Kazumi Saito	[15] [17] [21] [22] [24] [25] [26] [27] [30] [31] [32] [34] [36] [37] [38] [40] [42]
21	Jack Sklansky	[2]
22	Sean Stromsten	[26] [36]
23	Satoshi Suzuki	[2] [3] [18]
24	Tatsuki Taniguchi	[33] [39]
25	Joshua B. Tenenbaum	[26] [35] [36]
26	Shiro Usui	[33] [39]
27	Shinji Watanabe	[16] [28]
28	Takeshi Yamada	[21] [35] [43] [44]

Colors in the list of coauthors