Albert S. Berahas

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 30

Top Topics

Quadratic Optimization

Face Recognition

Complexity Bounds

Global Convergence

Top Venues

Optim. Methods Softw.

Publications

Sachin Garg, Albert S. Berahas, Michal Derezinski
Second-order Information Promotes Mini-Batch Robustness in Variance-Reduced Gradients. CoRR (2024)
Liyuan Cao, Albert S. Berahas, Katya Scheinberg
First- and second-order high probability complexity bounds for trust-region methods with noisy oracles. Math. Program. 207 (1) (2024)
Albert S. Berahas, Lindon Roberts, Fred Roosta
Non-Uniform Smoothness for Gradient Descent. Trans. Mach. Learn. Res. 2024 (2024)
Albert S. Berahas, Jiahao Shi, Zihong Yi, Baoyu Zhou
Accelerating stochastic sequential quadratic programming for equality constrained optimization using predictive variance reduction. Comput. Optim. Appl. 86 (1) (2023)
Albert S. Berahas, Lindon Roberts, Fred Roosta
Non-Uniform Smoothness for Gradient Descent. CoRR (2023)
Albert S. Berahas, Oumaima Sohab, Luís Nunes Vicente
Full-low evaluation methods for derivative-free optimization. Optim. Methods Softw. 38 (2) (2023)
Xubo Yue, Raed Al Kontar, Albert S. Berahas, Yang Liu, Zhenghao Zai, Kevin Edgar, Blake N. Johnson
Collaborative and Distributed Bayesian Optimization via Consensus: Showcasing the Power of Collaboration for Optimal Design. CoRR (2023)
Albert S. Berahas, Liyuan Cao, Krzysztof Choromanski, Katya Scheinberg
A Theoretical and Empirical Comparison of Gradient Approximations in Derivative-Free Optimization. Found. Comput. Math. 22 (2) (2022)
Albert S. Berahas, Frank E. Curtis, Baoyu Zhou
Limited-memory BFGS with displacement aggregation. Math. Program. 194 (1) (2022)
Albert S. Berahas, Majid Jahani, Peter Richtárik, Martin Takác
Quasi-Newton methods for machine learning: forget the past, just sample. Optim. Methods Softw. 37 (5) (2022)
Albert S. Berahas, Liyuan Cao, Katya Scheinberg
Global Convergence Rate Analysis of a Generic Line Search Algorithm with Noise. SIAM J. Optim. 31 (2) (2021)
Majid Jahani, MohammadReza Nazari, Rachael Tappenden, Albert S. Berahas, Martin Takác
SONIA: A Symmetric Blockwise Truncated Optimization Algorithm. AISTATS (2021)
Albert S. Berahas, Frank E. Curtis, Daniel P. Robinson, Baoyu Zhou
Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization. SIAM J. Optim. 31 (2) (2021)
Albert S. Berahas, Raghu Bollapragada, Ermin Wei
On the Convergence of Nested Decentralized Gradient Methods With Multiple Consensus and Gradient Steps. IEEE Trans. Signal Process. 69 (2021)
Albert S. Berahas, Frank E. Curtis, Daniel P. Robinson, Baoyu Zhou
Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization. CoRR (2020)
Zheng Shi, Nur Sila Gulgec, Albert S. Berahas, Shamim N. Pakzad, Martin Takác
Finite Difference Neural Networks: Fast Prediction of Partial Differential Equations. ICMLA (2020)
Albert S. Berahas, Martin Takác
A robust multi-batch L-BFGS method for machine learning. Optim. Methods Softw. 35 (1) (2020)
Majid Jahani, MohammadReza Nazari, Sergey Rusakov, Albert S. Berahas, Martin Takác
Scaling Up Quasi-newton Algorithms: Communication Efficient Distributed SR1. LOD (1) (2020)
Albert S. Berahas, Raghu Bollapragada, Jorge Nocedal
An investigation of Newton-Sketch and subsampled Newton methods. Optim. Methods Softw. 35 (4) (2020)
Zheng Shi, Nur Sila Gulgec, Albert S. Berahas, Shamim N. Pakzad, Martin Takác
Finite Difference Neural Networks: Fast Prediction of Partial Differential Equations. CoRR (2020)
Albert S. Berahas, Raghu Bollapragada, Nitish Shirish Keskar, Ermin Wei
Balancing Communication and Computation in Distributed Optimization. IEEE Trans. Autom. Control. 64 (8) (2019)
Albert S. Berahas, Richard H. Byrd, Jorge Nocedal
Derivative-Free Optimization of Noisy Functions via Quasi-Newton Methods. SIAM J. Optim. 29 (2) (2019)
Albert S. Berahas, Majid Jahani, Martin Takác
Quasi-Newton Methods for Deep Learning: Forget the Past, Just Sample. CoRR (2019)
Albert S. Berahas, Charikleia Iakovidou, Ermin Wei
Nested Distributed Gradient Methods with Adaptive Quantized Communication. CDC (2019)
Albert S. Berahas, Raghu Bollapragada, Jorge Nocedal
An Investigation of Newton-Sketch and Subsampled Newton Methods. CoRR (2017)
Albert S. Berahas, Martin Takác
A Robust Multi-Batch L-BFGS Method for Machine Learning. CoRR (2017)
Albert S. Berahas, Jorge Nocedal, Martin Takác
A Multi-Batch L-BFGS Method for Machine Learning. NIPS (2016)
Michael Iliadis, Leonidas Spinoulas, Albert S. Berahas, Haohong Wang, Aggelos K. Katsaggelos
Multi-model robust error correction for face recognition. ICIP (2016)
Albert S. Berahas, Jorge Nocedal, Martin Takác
A Multi-Batch L-BFGS Method for Machine Learning. CoRR (2016)
Nitish Shirish Keskar, Albert S. Berahas
adaQN: An Adaptive Quasi-Newton Algorithm for Training RNNs. ECML/PKDD (1) (2016)
Nitish Shirish Keskar, Albert S. Berahas
adaQN: An Adaptive Quasi-Newton Algorithm for Training RNNs. CoRR (2015)
Michael Iliadis, Leonidas Spinoulas, Albert S. Berahas, Haohong Wang, Aggelos K. Katsaggelos
Sparse representation and least squares-based classification in face recognition. EUSIPCO (2014)