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Showing items 1-10 of 15 (2 Page(s) Totally) 1 2 > >> View [10|25|50] records per page
國立臺灣科技大學 |
2020 |
A Proof on Equivalence of Stagewise Newton and Dreyfus's Successive Approximation Procedures
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Mizutani, E. |
國立臺灣科技大學 |
2019 |
A Note on Liao’s Recurrent Neural-Network Learning for Discrete Multi-stage Optimal Control Problems
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Mizutani, E. |
臺大學術典藏 |
2018-09-10T03:28:16Z |
Evolving color recipes
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Mizutani, E.; Takagi, H.; Ausl; er, D.M.; Jang, J.-S.R.; JYH-SHING JANG |
國立臺灣科技大學 |
2016 |
On a staged successive approximation procedure for approximate dynamic programming solutions to board game playing
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Mizutani, E. |
國立臺灣科技大學 |
2016 |
Totally model-free actor-critic recurrent neural-network reinforcement learning in non-Markovian domains
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Mizutani, E;Dreyfus, S. |
國立臺灣科技大學 |
2015 |
On Pantoja's problem allegedly showing a distinction between differential dynamic programming and stagewise Newton methods
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Mizutani, E. |
國立臺灣科技大學 |
2015 |
Finding all best ties by a K shortest paths method of Dreyfus in a general digraph for routing control
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Mizutani, E. |
國立臺灣科技大學 |
2014 |
A counterexample to a proposed dynamic programming algorithm for optimal bid construction in an auction-based fully distributed manufacturing system
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Mizutani, E. |
國立臺灣科技大學 |
2014 |
A note on dynamic programming formulations for scheduling job classes with changeover times on a single machine
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Mizutani, E. |
國立臺灣科技大學 |
2012 |
A block-approximate local Hessian-matrix analysis for CANFIS neuro-fuzzy modular network learning
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Mizutani, E. |
Showing items 1-10 of 15 (2 Page(s) Totally) 1 2 > >> View [10|25|50] records per page
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