@article{Indrapriyadarsini_Mahboubi_Ninomiya_Kamio_Asai_2022, title={A Stochastic Momentum Accelerated Quasi-Newton Method for Neural Networks (Student Abstract)}, volume={36}, url={https://ojs.aaai.org/index.php/AAAI/article/view/21623}, DOI={10.1609/aaai.v36i11.21623}, abstractNote={Incorporating curvature information in stochastic methods has been a challenging task. This paper proposes a momentum accelerated BFGS quasi-Newton method in both its full and limited memory forms, for solving stochastic large scale non-convex optimization problems in neural networks (NN).}, number={11}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Indrapriyadarsini, S. and Mahboubi, Shahrzad and Ninomiya, Hiroshi and Kamio, Takeshi and Asai, Hideki}, year={2022}, month={Jun.}, pages={12973-12974} }