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 | 2012 | |
|---|---|---|
| c14 |      | Yoshifusa Ito, Hiroyuki Izumi, Cidambi Srinivasan: Simultaneous Learning of Several Bayesian and Mahalanobis Discriminant Functions by a Neural Network with Memory Nodes. ICONIP (5) 2012: 25-33 |
| 2011 | ||
| c13 | | Yoshifusa Ito, Hiroyuki Izumi, Cidambi Srinivasan: A New Algorithm for Learning Mahalanobis Discriminant Functions by a Neural Network. ICONIP (2) 2011: 596-605 |
| c12 | | Yoshifusa Ito, Hiroyuki Izumi, Cidambi Srinivasan: Simultaneous learning of several Bayesian and Mahalanobis discriminant functions by a neural network with additional nodes. IJCNN 2011: 733-740 |
| 2009 | ||
| c11 | | Yoshifusa Ito, Hiroyuki Izumi, Cidambi Srinivasan: Learning of Mahalanobis Discriminant Functions by a Neural Network. ICONIP (1) 2009: 417-424 |
| 2008 | ||
| j8 | | Yoshifusa Ito: Simultaneous Approximations of Polynomials and Derivatives and Their Applications to Neural Networks. Neural Computation 20(11): 2757-2791 (2008) |
| c10 | | Yoshifusa Ito, Cidambi Srinivasan, Hiroyuki Izumi: Multi-category Bayesian Decision by Neural Networks. ICANN (1) 2008: 21-30 |
| 2007 | ||
| c9 | | Yoshifusa Ito, Cidambi Srinivasan, Hiroyuki Izumi: Learning of Bayesian Discriminant Functions by a Layered Neural Network. ICONIP (1) 2007: 238-247 |
| c8 | | Yoshifusa Ito, Crinivasan Srinivasan, Hiroyuki Izumi: A Neural Network having Fewer Inner Constants to be Trained and Bayesian Decision. IJCNN 2007: 2993-2998 |
| 2006 | ||
| c7 | | Yoshifusa Ito, Cidambi Srinivasan, Hiroyuki Izumi: Discriminant Analysis by a Neural Network with Mahalanobis Distance. ICANN (2) 2006: 350-360 |
| 2005 | ||
| j7 | | Yoshifusa Ito, Cidambi Srinivasan: Bayesian decision theory on three-layer neural networks. Neurocomputing 63: 209-228 (2005) |
| c6 | | Yoshifusa Ito, Cidambi Srinivasan, Hiroyuki Izumi: Bayesian Learning of Neural Networks Adapted to Changes of Prior Probabilities. ICANN (2) 2005: 253-259 |
| 2003 | ||
| j6 | | Yoshifusa Ito: Activation Functions Defined on Higher-Dimensional Spaces for Approximation on Compact Sets with and without Scaling. Neural Computation 15(9): 2199-2226 (2003) |
| c5 | | Yoshifusa Ito, Cidambi Srinivasan: Multicategory Bayesian Decision Using a Three-Layer Neural Network. ICANN 2003: 253-261 |
| 2002 | ||
| c4 | | Yoshifusa Ito: A Weak Condition on Linear Independence of Unscaled Shifts of a Function and Finite Mappings by Neural Networks. ICANN 2002: 337-343 |
| 2001 | ||
| c3 | | Yoshifusa Ito, Cidambi Srinivasan: Bayesian decision theory on three layered neural networks. ESANN 2001: 377-382 |
| c2 | | Yoshifusa Ito, Cidambi Srinivasan: Approximation of Bayesian Discriminant Function by Neural Networks in Terms of Kullback-Leibler Information. ICANN 2001: 135-140 |
| 2000 | ||
| c1 | | Yoshifusa Ito: Surface-Tracing Approximation by Basis Functions and Its Application to Neural Networks. IJCNN (4) 2000: 227-231 |
| 1996 | ||
| j5 | | |
| 1994 | ||
| j4 | | Yoshifusa Ito: Approximation Capability of Layered Neural Networks with Sigmoid Units on Two Layers. Neural Computation 6(6): 1233-1243 (1994) |
| 1992 | ||
| j3 | | Yoshifusa Ito: Approximation of continuous functions on Rd by linear combinations of shifted rotations of a sigmoid function with and without scaling. Neural Networks 5(1): 105-115 (1992) |
| 1991 | ||
| j2 | | Yoshifusa Ito: Representation of functions by superpositions of a step or sigmoid function and their applications to neural network theory. Neural Networks 4(3): 385-394 (1991) |
| j1 | | Yoshifusa Ito: Approximation of functions on a compact set by finite sums of a sigmoid function without scaling. Neural Networks 4(6): 817-826 (1991) |
| 1 | Hiroyuki Izumi | |
| 2 | Cidambi Srinivasan | |
| 3 | Crinivasan Srinivasan |
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