| 2007 |
|---|
| 45 | EE | Sumio Watanabe:
Almost All Learning Machines are Singular.
FOCI 2007: 383-388 |
| 44 | EE | Kenji Nagata,
Sumio Watanabe:
Analysis of Exchange Ratio for Exchange Monte Carlo Method.
FOCI 2007: 434-439 |
| 43 | EE | Shinichi Nakajima,
Sumio Watanabe:
Generalization Error of Automatic Relevance Determination.
ICANN (1) 2007: 1-10 |
| 42 | EE | Takeshi Matsuda,
Sumio Watanabe:
On a Singular Point to Contribute to a Learning Coefficient and Weighted Resolution of Singularities.
ICANN (1) 2007: 11-18 |
| 41 | EE | Yu Nishiyama,
Sumio Watanabe:
Theoretical Analysis of Accuracy of Gaussian Belief Propagation.
ICANN (1) 2007: 29-38 |
| 40 | EE | Kenji Nagata,
Sumio Watanabe:
Algebraic Geometric Study of Exchange Monte Carlo Method.
ICANN (1) 2007: 687-696 |
| 39 | EE | Ryosuke Iriguchi,
Sumio Watanabe:
Estimation of Poles of Zeta Function in Learning Theory Using Padé Approximation.
ICANN (1) 2007: 88-97 |
| 38 | EE | Keisuke Yamazaki,
Motoaki Kawanabe,
Sumio Watanabe,
Masashi Sugiyama,
Klaus-Robert Müller:
Asymptotic Bayesian generalization error when training and test distributions are different.
ICML 2007: 1079-1086 |
| 37 | EE | Miki Aoyagi,
Sumio Watanabe:
Resolution of Singularities and Stochastic Complexity of Complete Bipartite Graph-Type Spin Model in Bayesian Estimation.
MDAI 2007: 443-454 |
| 36 | | Takeshi Matsuda,
Sumio Watanabe:
The Calculation Method of Learning Coefficients by Weighted Resolution of Singularities.
MLMTA 2007: 177-181 |
| 35 | EE | Sumio Watanabe:
Equations of States in Singular Statistical Estimation
CoRR abs/0712.0653: (2007) |
| 34 | EE | Shinichi Nakajima,
Sumio Watanabe:
Variational Bayes Solution of Linear Neural Networks and Its Generalization Performance.
Neural Computation 19(4): 1112-1153 (2007) |
| 33 | EE | Kazuho Watanabe,
Sumio Watanabe:
Stochastic complexities of general mixture models in variational Bayesian learning.
Neural Networks 20(2): 210-219 (2007) |
| 32 | EE | Kazuho Watanabe,
Sumio Watanabe:
Stochastic complexity for mixture of exponential families in generalized variational Bayes.
Theor. Comput. Sci. 387(1): 4-17 (2007) |
| 2006 |
|---|
| 31 | EE | Takeshi Matsuda,
Sumio Watanabe:
Analytic Equivalence of Bayes a Posteriori Distributions.
ICANN (1) 2006: 113-121 |
| 30 | EE | Shinichi Nakajima,
Sumio Watanabe:
Analytic Solution of Hierarchical Variational Bayes in Linear Inverse Problem.
ICANN (2) 2006: 240-249 |
| 29 | EE | Keisuke Yamazaki,
Kenji Nagata,
Sumio Watanabe,
Klaus-Robert Müller:
A Model Selection Method Based on Bound of Learning Coefficient.
ICANN (2) 2006: 371-380 |
| 28 | EE | Tikara Hosino,
Kazuho Watanabe,
Sumio Watanabe:
Free Energy of Stochastic Context Free Grammar on Variational Bayes.
ICONIP (1) 2006: 407-416 |
| 27 | EE | Yu Nishiyama,
Sumio Watanabe:
Asymptotic Behavior of Stochastic Complexity of Complete Bipartite Graph-Type Boltzmann Machines.
ICONIP (1) 2006: 417-426 |
| 26 | EE | Shingo Takamatsu,
Shinichi Nakajima,
Sumio Watanabe:
Localized Bayes Estimation for Non-identifiable Models.
ICONIP (1) 2006: 650-659 |
| 25 | EE | Kenji Nagata,
Sumio Watanabe:
Generalization Performance of Exchange Monte Carlo Method for Normal Mixture Models.
IDEAL 2006: 125-132 |
| 24 | EE | Kazuho Watanabe,
Motoki Shiga,
Sumio Watanabe:
Upper Bounds for Variational Stochastic Complexities of Bayesian Networks.
IDEAL 2006: 139-146 |
| 23 | EE | Shinichi Nakajima,
Sumio Watanabe:
Generalization Performance of Subspace Bayes Approach in Linear Neural Networks.
IEICE Transactions 89-D(3): 1128-1138 (2006) |
| 22 | EE | Kazuho Watanabe,
Sumio Watanabe:
Stochastic Complexities of Gaussian Mixtures in Variational Bayesian Approximation.
Journal of Machine Learning Research 7: 625-644 (2006) |
| 2005 |
|---|
| 21 | EE | Kazuho Watanabe,
Sumio Watanabe:
Stochastic Complexity for Mixture of Exponential Families in Variational Bayes.
ALT 2005: 107-121 |
| 20 | EE | Shinichi Nakajima,
Sumio Watanabe:
Generalization Error of Linear Neural Networks in an Empirical Bayes Approach.
IJCAI 2005: 804-810 |
| 19 | EE | Kazuho Watanabe,
Sumio Watanabe:
Variational Bayesian Stochastic Complexity of Mixture Models.
NIPS 2005 |
| 18 | EE | Miki Aoyagi,
Sumio Watanabe:
Stochastic complexities of reduced rank regression in Bayesian estimation.
Neural Networks 18(7): 924-933 (2005) |
| 17 | EE | Sumio Watanabe:
Algebraic geometry of singular learning machines and symmetry of generalization and training errors.
Neurocomputing 67: 198-213 (2005) |
| 16 | EE | Keisuke Yamazaki,
Sumio Watanabe:
Algebraic geometry and stochastic complexity of hidden Markov models.
Neurocomputing 69(1-3): 62-84 (2005) |
| 2004 |
|---|
| 15 | EE | Kazuho Watanabe,
Sumio Watanabe:
Estimation of the Data Region Using Extreme-Value Distributions.
ALT 2004: 206-220 |
| 14 | EE | Keisuke Yamazaki,
Sumio Watanabe:
Newton Diagram and Stochastic Complexity in Mixture of Binomial Distributions.
ALT 2004: 350-364 |
| 2003 |
|---|
| 13 | | Keisuke Yamazaki,
Sumio Watanabe:
Stochastic Complexity of Bayesian Networks.
UAI 2003: 592-599 |
| 12 | EE | Sumio Watanabe,
Shun-ichi Amari:
Learning Coefficients of Layered Models When the True Distribution Mismatches the Singularities.
Neural Computation 15(5): 1013-1033 (2003) |
| 11 | EE | Keisuke Yamazaki,
Sumio Watanabe:
Singularities in mixture models and upper bounds of stochastic complexity.
Neural Networks 16(7): 1029-1038 (2003) |
| 2002 |
|---|
| 10 | EE | Sumio Watanabe,
Shun-ichi Amari:
The Effect of Singularities in a Learning Machine when the True Parameters Do Not Lie on such Singularities.
NIPS 2002: 391-398 |
| 2001 |
|---|
| 9 | | Sumio Watanabe:
Algebraic Analysis for Nonidentifiable Learning Machines.
Neural Computation 13(4): 899-933 (2001) |
| 8 | EE | Sumio Watanabe:
Algebraic geometrical methods for hierarchical learning machines.
Neural Networks 14(8): 1049-1060 (2001) |
| 2000 |
|---|
| 7 | | Sumio Watanabe:
Algebraic Information Geometry for Learning Machines with Singularities.
NIPS 2000: 329-335 |
| 1999 |
|---|
| 6 | EE | Sumio Watanabe:
Algebraic Analysis for Singular Statistical Estimation.
ATL 1999: 39-50 |
| 5 | EE | Sumio Watanabe:
Algebraic Analysis for Non-regular Learning Machines.
NIPS 1999: 356-362 |
| 1998 |
|---|
| 4 | | Sumio Watanabe:
Inequalities of Generalization Errors for Layered Neural Networks in Bayesian Learning.
ICONIP 1998: 59-62 |
| 1996 |
|---|
| 3 | EE | Shin Ishi,
Kenji Fukumizu,
Sumio Watanabe:
A network of chaotic elements for information processing.
Neural Networks 9(1): 25-40 (1996) |
| 1993 |
|---|
| 2 | EE | Sumio Watanabe:
An Optimization Method of Layered Neural Networks based on the Modified Information Criterion.
NIPS 1993: 293-302 |
| 1 | EE | Sumio Watanabe:
Solvable Models of Artificial Neural Networks.
NIPS 1993: 423-430 |
