Author:
Keskar Nitish Shirish,Berahas Albert S.
Publisher
Springer International Publishing
Reference30 articles.
1. Bengio, Y., Simard, P., Frasconi, P.: Learning long-term dependencies with gradient descent is difficult. Neural Netw. IEEE Trans. 5(2), 157–166 (1994)
2. Bengio, Y., Goodfellow, I., Courville, A.: Deep learning (2016). Book in preparation for MIT Press. http://www.deeplearningbook.org
3. Byrd, R.H., Hansen, S.L., Nocedal, J., Singer, Y.: A stochastic quasi-Newton method for large-scale optimization. SIAM J. Optim. 26(2), 1008–1031 (2016)
4. Cho, K., Van Merriënboer, B., Gülçehre, Ç., Bahdanau, D., Bougares, F., Schwenk, H., Bengio, Y.: Learning phrase representations using RNN encoder-decoder for statistical machine translation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1724–1734. Association for Computational Linguistics, Doha, Qatar, October 2014
5. Duchi, J., Hazan, E., Singer, Y.: Adaptive subgradient methods for online learning and stochastic optimization. J. Mach. Learn. Res. 12, 2121–2159 (2011)
Cited by
9 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Adaptive Quasi-Newton Algorithm for Remote Sensing;2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS);2023-05-12
2. An Overview of Stochastic Quasi-Newton Methods for Large-Scale Machine Learning;Journal of the Operations Research Society of China;2023-02-25
3. Stable Learning Algorithm Using Reducibility for Recurrent Neural Networks;Artificial Neural Networks and Machine Learning – ICANN 2023;2023
4. Quasi-Newton methods for machine learning: forget the past, just sample;Optimization Methods and Software;2021-10-15
5. Full-waveform inversion using adaptive quasi-Newton optimization;First International Meeting for Applied Geoscience & Energy Expanded Abstracts;2021-09-01