Eiji Mizutani

37 papers B 12C 1Journal 14Unranked 10
YearRankTypeTitle / Venue / Authors
2024 J jnl
On Stage-Wise Backpropagation for Improving Cheng's Method for Fully Connected Cascade Networks.
Neural Process. Lett.
Eiji Mizutani, Naoyuki Kubota, Tam Chi Truong
2023 J jnl
A note on a single-shift days-off scheduling problem with sequence-dependent labor costs.
J. Sched.
Eiji Mizutani, Kevin Alexander Sánchez Galeano
2023 J jnl
A tutorial on the art of dynamic programming for some issues concerning Bellman's principle of optimality.
ICT Express
Eiji Mizutani, Stuart Dreyfus
2021 J jnl
On using dynamic programming for time warping in pattern recognition.
Inf. Sci.
Eiji Mizutani, Stuart Dreyfus
2020 J jnl
A Proof on Equivalence of Stagewise Newton and Dreyfus's Successive Approximation Procedures.
IEEE Trans. Autom. Control.
Eiji Mizutani
2019 J jnl
A Note on Liao's Recurrent Neural-Network Learning for Discrete Multi-stage Optimal Control Problems.
Neural Process. Lett.
Eiji Mizutani
2019 — conf
On Two New Dynamic-Programming Procedures As Efficient As the Wagner-Whitin Regeneration-Point Type in Dynamic Lot Sizing.
IEEM
Eiji Mizutani, Brigitte Trista
2017 J jnl
Totally model-free actor-critic recurrent neural-network reinforcement learning in non-Markovian domains.
Ann. Oper. Res.
Eiji Mizutani, Stuart E. Dreyfus
2015 J jnl
On Pantoja's problem allegedly showing a distinction between differential dynamic programming and stagewise Newton methods.
Int. J. Control
Eiji Mizutani
2015 — conf
On a staged successive approximation procedure for approximate dynamic programming solutions to board game playing.
IEEM
Eiji Mizutani
2012 B conf
A block-approximate local Hessian-matrix analysis for CANFIS neuro-fuzzy modular network learning.
FUZZ-IEEE
Eiji Mizutani
2011 — conf
On exploiting sparsity in CANFIS neuro-fuzzy modular network learning by second-order stagewise backpropagation.
FSKD
Eiji Mizutani
2011 B conf
On improving trust-region variable projection algorithms for separable nonlinear least squares learning.
IJCNN
Eiji Mizutani, James Demmel
2011 B conf
Online neuro-fuzzy CANFIS hidden-node teaching.
FUZZ-IEEE
Eiji Mizutani, Jing-Yun Carey Fan
2010 — conf
An analysis on negative curvature induced by singularity in multi-layer neural-network learning.
NIPS
Eiji Mizutani, Stuart Dreyfus
2008 J jnl
Corrigendum to: "Second-order stagewise backpropagation for Hessian-matrix analyses and investigation of negative curvature" [Neural Netw. 21(2-3) (2008) 193-203]
Neural Networks
Eiji Mizutani, Stuart E. Dreyfus
2008 J jnl
Second-order stagewise backpropagation for Hessian-matrix analyses and investigation of negative curvature.
Neural Networks
Eiji Mizutani, Stuart E. Dreyfus
2007 B conf
On exploiting symmetry for multilayer perceptron learning.
IJCNN
Eiji Mizutani, Jing-Yun Carey Fan
2007 B conf
On practical use of stagewise second-order backpropagation for multi-stage neural-network learning.
IJCNN
Eiji Mizutani, Stuart Dreyfus
2006 B conf
On derivation of stagewise second-order backpropagation by invariant imbedding for multi-stage neural-network learning.
IJCNN
Eiji Mizutani, Stuart Dreyfus
2005 B conf
Second-order backpropagation algorithms for a stagewise-partitioned separable Hessian matrix.
IJCNN
Eiji Mizutani, Stuart E. Dreyfus, James Weldon Demmel
2005 C conf
Stagewise Newton, differential dynamic programming, and neighboring optimum control for neural-network learning.
ACC
Eiji Mizutani, Stuart E. Dreyfus
2004 B conf
Two stochastic dynamic programming problems by model-free actor-critic recurrent-network learning in non-Markovian settings.
IJCNN
Eiji Mizutani, Stuart E. Dreyfus
2003 — conf
Iterative Scaled Trust-Region Learning in Krylov Subspaces via Pearlmutter's Implicit Sparse Hessian-Vector Multiply.
NIPS
Eiji Mizutani, James Demmel
2003 B conf
On sparsity-exploiting memory-efficient trust-region regularized nonlinear least squares algorithms for neural-network learning.
IJCNN
Eiji Mizutani, James Weldon Demmel
2003 J jnl
On structure-exploiting trust-region regularized nonlinear least squares algorithms for neural-network learning.
Neural Networks
Eiji Mizutani, James Demmel
2003 — conf
On using discretized Cohen-Grossberg node dynamics for model-free actor-critic neural learning in non-Markovian domains.
CIRA
Eiji Mizutani, Stuart E. Dreyfus
2002 B conf
Fuzzy mixtures of complementary local experts: towards neuro-fuzzy modular networks.
FUZZ-IEEE
Eiji Mizutani, Kenichi Nishio
2002 J jnl
Multi-illuminant color reproduction for electronic cameras via CANFIS neuro-fuzzy modular network device characterization.
IEEE Trans. Neural Networks
Eiji Mizutani, Kenichi Nishio
2000 J jnl
Evolving color recipes.
IEEE Trans. Syst. Man Cybern. Part C
Eiji Mizutani, Hideyuki Takagi, David M. Auslander, Jyh-Shing Roger Jang
2000 — conf
On Derivation of MLP Backpropagation from the Kelley-Bryson Optimal-Control Gradient Formula and Its Application.
IJCNN (2)
Eiji Mizutani, Stuart E. Dreyfus, Kenichi Nishio
2000 — conf
On Iterative Krylov-Dogleg Trust-Region Steps for Solving Neural Networks Nonlinear Least Squares Problems.
NIPS
Eiji Mizutani, James Demmel
1999 B conf
Powell's dogleg trust-region steps with the quasi-Newton augmented Hessian for neural nonlinear least-squares learning.
IJCNN
Eiji Mizutani
1999 B conf
Sample path-based policy-only learning by actor neural networks.
IJCNN
Eiji Mizutani
1997 J jnl
Neuro-Fuzzy and Soft Computing-A Computational Approach to Learning and Machine Intelligence [Book Review].
IEEE Trans. Autom. Control.
Jyh-Shing Roger Jang, Chuen-Tsai Sun, Eiji Mizutani
1995 — conf
Coactive neural fuzzy modeling.
ICNN
Eiji Mizutani, Jyh-Shing Roger Jang
1995 — conf
Coactive neuro-fuzzy modelling for colour recipe prediction.
ICNN
Eiji Mizutani, Jyh-Shing Roger Jang, Kenichi Nishio, Hideyuki Takagi, David M. Auslander