Eiji Mizutani - researchr alias

researchr

You are not signed in
Sign in
Sign up

Viewing Publication 1 - 32 from 32

2023

A note on a single-shift days-off scheduling problem with sequence-dependent labor costsEiji Mizutani, Kevin Alexander Sánchez Galeano. scheduling, 26(3):315-329, June 2023. [doi]

A tutorial on the art of dynamic programming for some issues concerning Bellman's principle of optimalityEiji Mizutani, Stuart Dreyfus. ict-express, 9(6):1144-1161, December 2023. [doi]

2021

On using dynamic programming for time warping in pattern recognitionEiji Mizutani, Stuart Dreyfus. isci, 580:684-704, 2021. [doi]

2020

A Proof on Equivalence of Stagewise Newton and Dreyfus's Successive Approximation ProceduresEiji Mizutani. tac, 65(6):2716-2723, 2020. [doi]

2019

A Note on Liao's Recurrent Neural-Network Learning for Discrete Multi-stage Optimal Control ProblemsEiji Mizutani. npl, 50(3):3009-3018, 2019. [doi]

On Two New Dynamic-Programming Procedures As Efficient As the Wagner-Whitin Regeneration-Point Type in Dynamic Lot SizingEiji Mizutani, Brigitte Trista. ieem 2019: 1290-1294 [doi]

2017

Totally model-free actor-critic recurrent neural-network reinforcement learning in non-Markovian domainsEiji Mizutani, Stuart E. Dreyfus. anor, 258(1):107-131, 2017. [doi]

2015

On a staged successive approximation procedure for approximate dynamic programming solutions to board game playingEiji Mizutani. ieem 2015: 529-533 [doi]

2012

A block-approximate local Hessian-matrix analysis for CANFIS neuro-fuzzy modular network learningEiji Mizutani. fuzzIEEE 2012: 1-8 [doi]

2011

On exploiting sparsity in CANFIS neuro-fuzzy modular network learning by second-order stagewise backpropagationEiji Mizutani. fskd 2011: 202-206 [doi]

Online neuro-fuzzy CANFIS hidden-node teachingEiji Mizutani, Jing-Yun Carey Fan. fuzzIEEE 2011: 2559-2565 [doi]

On improving trust-region variable projection algorithms for separable nonlinear least squares learningEiji Mizutani, James Demmel. ijcnn 2011: 397-404 [doi]

2010

An analysis on negative curvature induced by singularity in multi-layer neural-network learningEiji Mizutani, Stuart Dreyfus. nips 2010: 1669-1677 [doi]

2008

Corrigendum to: Second-order stagewise backpropagation for Hessian-matrix analyses and investigation of negative curvature [Neural Netw. 21(2-3) (2008) 193-203]Eiji Mizutani, Stuart E. Dreyfus. NN, 21(9):1418, 2008. [doi]

Second-order stagewise backpropagation for Hessian-matrix analyses and investigation of negative curvatureEiji Mizutani, Stuart E. Dreyfus. NN, 21(2-3):193-203, 2008. [doi]

2007

On exploiting symmetry for multilayer perceptron learningEiji Mizutani, Jing-Yun Carey Fan. ijcnn 2007: 2857-2862 [doi]

On practical use of stagewise second-order backpropagation for multi-stage neural-network learningEiji Mizutani, Stuart Dreyfus. ijcnn 2007: 1302-1307 [doi]

2006

On derivation of stagewise second-order backpropagation by invariant imbedding for multi-stage neural-network learningEiji Mizutani, Stuart Dreyfus. ijcnn 2006: 4762-4769 [doi]

2005

Stagewise Newton, differential dynamic programming, and neighboring optimum control for neural-network learningEiji Mizutani, Stuart E. Dreyfus. amcc 2005: 1331-1336 [doi]

2003

On using discretized Cohen-Grossberg node dynamics for model-free actor-critic neural learning in non-Markovian domainsEiji Mizutani, Stuart E. Dreyfus. cira 2003: 1-6 [doi]

Iterative Scaled Trust-Region Learning in Krylov Subspaces via Pearlmutter s Implicit Sparse Hessian-Vector MultiplyEiji Mizutani, James Demmel. nips 2004: 209-216 [doi]

On structure-exploiting trust-region regularized nonlinear least squares algorithms for neural-network learningEiji Mizutani, James Demmel. NN, 16(5-6):745-753, 2003. [doi]

2002

Multi-illuminant color reproduction for electronic cameras via CANFIS neuro-fuzzy modular network device characterizationEiji Mizutani, Kenichi Nishio. tnn, 13(4):1009-1022, 2002. [doi]

Fuzzy mixtures of complementary local experts: towards neuro-fuzzy modular networksEiji Mizutani, Kenichi Nishio. fuzzIEEE 2002: 1192-1197 [doi]

2000

On Derivation of MLP Backpropagation from the Kelley-Bryson Optimal-Control Gradient Formula and Its ApplicationEiji Mizutani, Stuart E. Dreyfus, Kenichi Nishio. ijcnn 2000: 167-172 [doi]

Evolving color recipesEiji Mizutani, Hideyuki Takagi, David M. Auslander, Jyh-Shing Roger Jang. tsmc, 30(4):537-550, 2000.

On Iterative Krylov-Dogleg Trust-Region Steps for Solving Neural Networks Nonlinear Least Squares ProblemsEiji Mizutani, James Demmel. nips 2001: 605-611

1999

Powell's dogleg trust-region steps with the quasi-Newton augmented Hessian for neural nonlinear least-squares learningEiji Mizutani. ijcnn 1999: 1239-1244 [doi]

Sample path-based policy-only learning by actor neural networksEiji Mizutani. ijcnn 1999: 1245-1250 [doi]

1997

Neuro-Fuzzy and Soft Computing-A Computational Approach to Learning and Machine Intelligence [Book Review]Jyh-Shing Roger Jang, Chuen-Tsai Sun, Eiji Mizutani. tac, 42(10):1482-1484, 1997. [doi]

1995

Coactive neuro-fuzzy modelling for colour recipe predictionEiji Mizutani, Jyh-Shing Roger Jang, Kenichi Nishio, Hideyuki Takagi, David M. Anslander. icnn 1995: 2252-2257 [doi]

Coactive neural fuzzy modelingEiji Mizutani, Jyh-Shing Roger Jang. icnn 1995: 760-765 [doi]

Sign in or sign up to see more results.

runs on WebDSL