Albert S. Berahas
Albert S. Berahas
Postdoctoral Research Fellow, Lehigh University
Verified email at - Homepage
TitleCited byYear
A multi-batch L-BFGS method for machine learning
AS Berahas, J Nocedal, M Takác
Advances in Neural Information Processing Systems, 1055-1063, 2016
An investigation of Newton-sketch and subsampled Newton methods
AS Berahas, R Bollapragada, J Nocedal
arXiv preprint arXiv:1705.06211, 2017
adaqn: An adaptive quasi-newton algorithm for training rnns
NS Keskar, AS Berahas
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2016
Balancing communication and computation in distributed optimization
A Berahas, R Bollapragada, NS Keskar, E Wei
IEEE Transactions on Automatic Control, 2018
Sparse representation and least squares-based classification in face recognition
M Iliadis, L Spinoulas, AS Berahas, H Wang, AK Katsaggelos
2014 22nd European Signal Processing Conference (EUSIPCO), 526-530, 2014
Derivative-free optimization of noisy functions via quasi-Newton methods
AS Berahas, RH Byrd, J Nocedal
SIAM Journal on Optimization 29 (2), 965-993, 2019
A robust multi-batch l-bfgs method for machine learning
AS Berahas, M Takáč
arXiv preprint arXiv:1707.08552, 2017
Multi-model robust error correction for face recognition
M Iliadis, L Spinoulas, AS Berahas, H Wang, AK Katsaggelos
2016 IEEE International Conference on Image Processing (ICIP), 3229-3233, 2016
Nested Distributed Gradient Methods with Adaptive Quantized Communication
AS Berahas, C Iakovidou, E Wei
arXiv preprint arXiv:1903.08149, 2019
Limited-Memory BFGS with Displacement Aggregation
AS Berahas, FE Curtis, B Zhou
arXiv preprint arXiv:1903.03471, 2019
Quasi-Newton Methods for Deep Learning: Forget the Past, Just Sample
AS Berahas, M Jahani, M Takáč
arXiv preprint arXiv:1901.09997, 2019
Methods for Large Scale Nonlinear and Stochastic Optimization
AS Berahas
Northwestern University, 2018
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