H. Ninomiya

发表

Audio-visual speech recognition using deep bottleneck features and high-performance lipreading

Satoshi Tamura, Satoru Hayamizu, Kazuya Takeda, 2015, 2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA).

Special Section on Recent Advances in Machine Learning for Spoken Language Processing Investigation of DNN-Based Audio-Visual Speech Recognition

K. Takeda, N. Kitaoka, S. Hayamizu, 2016 .

Invited Paper Three-Dimensional Module Packing Using 3DBSG Structure

Hideki Asai, Hiroshi Ninomiya, Hirokazu Yamagishi, 2005 .

A Neuro-Based Optimization Algorithm for Rectangular Puzzles(Special Section of Papers Selected from ITC-CSCC'97)

Hideki Asai, Hiroshi Ninomiya, Hiroyuki Yamamoto, 1998 .

Neuro-Based Optimization Algorithm for Cubic Puzzles

Hideki Asai, Hiroyuki Yamamoto, Hiroshi Ninomiya, 1996 .

On the Practical Robustness of the Nesterov's Accelerated Quasi-Newton Method

H. Ninomiya, H. Asai, T. Kamio, 2022, AAAI.

Neuro-based tiling algorithm using fitting violation function of polyominoes

H. Ninomiya, T. Nakayama, H. Asai, 1996, 1996 IEEE International Symposium on Circuits and Systems. Circuits and Systems Connecting the World. ISCAS 96.

An efficient algorithm for spatiotemporal pattern analysis of multivalued neural networks

H. Ninomiya, T. Yoneyama, A. Kamo, 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).

A Novel Training Algorithm based on Limited-Memory quasi-Newton Method with Nesterov’s Accelerated Gradient in Neural Networks and its Application to Highly-Nonlinear Modeling of Microwave Circuit

H. Ninomiya, Shahrzad Mahboubi, 2019 .

Discrete Walsh Transform by Linear Programming Neural Net

Hideki Asai, Takeshi Kamio, Hiroshi Ninomiya, 1994 .

A Robust Quasi-Newton Training with Adaptive Momentum for Microwave Circuit Models in Neural Networks

Hideki Asai, Hiroshi Ninomiya, Shahrzad Mahboubi, 2020 .

Robust Training of Multilayer Neural Networks Using Parameterized Online Quasi-Newton Algorithm

Hiroshi Ninomiya, H. Ninomiya, 2011, 2011 10th International Conference on Machine Learning and Applications and Workshops.

Parameterized online quasi-Newton training for high-nonlinearity function approximation using multilayer neural networks

Hiroshi Ninomiya, H. Ninomiya, 2011, The 2011 International Joint Conference on Neural Networks.

Accelerating Symmetric Rank-1 Quasi-Newton Method with Nesterov's Gradient for Training Neural Networks

H. Ninomiya, H. Asai, T. Kamio, 2021, Algorithms.

Design method of neural networks for limit cycle generator

Hideki Asai, Teru Yoneyama, Hiroshi Ninomiya, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

A study of Hopfield neural networks with external noises

Hideki Asai, T. Kamio, Hiroshi Ninomiya, 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

Implementation of a Modified Nesterov's Accelerated Quasi-Newton Method on Tensorflow

Hideki Asai, S. Indrapriyadarsini, Hiroshi Ninomiya, 2018, 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA).

A hybrid global/local optimization technique for robust training of microwave neural network models

Hiroshi Ninomiya, H. Ninomiya, 2009, 2009 IEEE Congress on Evolutionary Computation.

A Stochastic Variance Reduced Nesterov's Accelerated Quasi-Newton Method

Hideki Asai, S. Indrapriyadarsini, Hiroshi Ninomiya, 2019, 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA).

Analog neuro‐based approach to tiling problem using fitting function of polyominoes

Hideki Asai, Hiroshi Ninomiya, Takeshi Nakayama, 2000 .

Application of neuro-based optimization algorithm to three dimensional cylindric puzzles

H. Asai, Hiroyuki Yamamoto, Hiroshi Ninomiya, 1997, Proceedings of International Conference on Neural Networks (ICNN'97).

Tiling algorithm with fitting violation function for analog neural array

H. Ninomiya, Takeshi Nakayama, H. Asai, 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

Distributed robust training of multilayer neural netwroks using normalized risk-averting error

Hiroshi Ninomiya, H. Ninomiya, 2014, 2014 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB).

A Nesterov's Accelerated quasi-Newton method for Global Routing using Deep Reinforcement Learning pdf

Hideki Asai, Takeshi Kamio, S. Indrapriyadarsini, 2020, ArXiv.

Deep Manifold Embedding for 3D Object Pose Estimation

Hiroshi Murase, Daisuke Deguchi, Ichiro Ide, 2017, VISIGRAPP.

A novel quasi-Newton-based optimization for neural network training incorporating Nesterov's accelerated gradient

Hiroshi Ninomiya, H. Ninomiya, 2017 .

Momentum Acceleration of Quasi-Newton Training for Neural Networks

Hideki Asai, S. Indrapriyadarsini, Hiroshi Ninomiya, 2019, PRICAI.

Dynamic sample size selection based quasi-Newton training for highly nonlinear function approximation using multilayer neural networks

Hiroshi Ninomiya, H. Ninomiya, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

An Improved Online quasi-Newton method for robust training and its application to microwave neural network models

Hiroshi Ninomiya, H. Ninomiya, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Momentum acceleration of quasi-Newton based optimization technique for neural network training

Hideki Asai, Hiroshi Ninomiya, Shahrzad Mahboubi, 2021, Nonlinear Theory and Its Applications, IEICE.

Robust Training of Feedforward Neural Networks Using Combined Online/Batch Quasi-Newton Techniques

Hiroshi Ninomiya, H. Ninomiya, 2012, ICANN.

Integration of deep bottleneck features for audio-visual speech recognition

Satoshi Tamura, Kazuya Takeda, Norihide Kitaoka, 2015, INTERSPEECH.