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- Fred Roosta
Dr Fred Roosta
Lecturer
The University of Queensland
2017 -- Present:
- Faculty in the School of Mathematics and Physics at the University of Queensland (Brisbane, Australia)
- Distinguished Research Scholar in the International Computer Science Institute (ICSI) (Berkeley, USA)
2015 -- 2017:
- Postdoctoral fellow in the Department of Statistics at UC Berkeley (Berkeley, USA, Advisor: Prof. Michael Mahoney)
2010 -- 2015:
- PhD student in the Computer Science Department at the University of British Columbia (Vancouver, Canada, Advisor: Prof. Uri Ascher)
Publications
Book Chapters
Ye, N., Roosta-Khorasani F., Cui T., De Gier J., Praeger C. E., & Tao T.
(2019). Optimization Methods for Inverse Problems.
(Wood, D., Ed.).2017 MATRIX Annals. doi: 10.1007/978-3-030-04161-8_9
Invited talks, refereed proceedings and other conference outputs
Wang, S., Roosta-Khorasani F., Xu P., & Mahoney M. W.
(2018). GIANT: Globally Improved Approximate Newton Method for Distributed Optimization.
(Bengio, S.., Wallach H.., Larochelle H.., Grauman K.., Cesa-Bianchi N.., & Garnett R.., Ed.).Advances in Neural Information Processing Systems 31. 2338–2348.
Tsuchida, R., Roosta-Khorasani F., & Gallagher M.
(2018). Invariance of Weight Distributions in Rectified MLPs.
(Dy, J., & Krause A., Ed.).Proceedings of the 35th International Conference on Machine Learning. 80, 4995–5004.
Levin, K., Roosta-Khorasani F., Mahoney M., & Priebe C.
(2018). Out-of-sample extension of graph adjacency spectral embedding.
(Dy, J., & Krause A., Ed.).Proceedings of the 35th International Conference on Machine Learning. 80, 2975–2984.
Cheng, X., Roosta-Khorasani F., Palombo S., Bartlett P.L., & Mahoney M.
(2018). FLAG n’ FLARE: Fast Linearly-Coupled Adaptive Gradient Methods.
(Storkey, A., & Perez-Cruz F., Ed.).Conference on Artificial Intelligence and Statistics. 84, 404–414.
Journal Articles
Yao, Z., Xu P., Roosta-Khorasani F., & Mahoney M. W.
(2018). Inexact non-convex Newton-type methods.
arXiv preprint arXiv:1802.06925.
Tsuchida, R., Roosta-Khorasani F., & Gallagher M.
(2018). Exchangeability and Kernel Invariance in Trained MLPs.
arXiv preprint arXiv:1810.08351.
Fang, C-H., Kylasa S. B., Roosta-Khorasani F., Mahoney M. W., & Grama A.
(2018). Distributed Second-order Convex Optimization.
arXiv preprint arXiv:1807.07132.
Kylasa, S. B., Roosta-Khorasani F., Mahoney M. W., & Grama A.
(2018). GPU Accelerated Sub-Sampled Newton's Method.
arXiv preprint arXiv:1802.09113.
Publicly available softwares
Wang, S., Roosta-Khorasani F., Xu P., & Mahoney M. W.
(2018). Spark GIANT.
Fang, C-H., Kylasa S. B., Roosta-Khorasani F., Mahoney M. W., & Grama A.
(2018). Newton ADMM.
Technical reports and unrefereed outputs
Roosta-Khorasani, F., Liu Y., Xu P., & Mahoney M. W.
(2018). Newton-MR: Newton's Method Without Smoothness or Convexity.
