Albert S. Berahas

University of Michigan — United States

Computer Science · Physical Sciences

12h-index560citations63works1.22yr avg
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Research Topics

Stochastic Gradient Optimization Techniques(31), Sparse and Compressive Sensing Techniques(29), Advanced Optimization Algorithms Research(21), Distributed Control Multi-Agent Systems(12), Advanced Multi-Objective Optimization Algorithms(6)

Publications63 total

Exploiting negative curvature in conjunction with adaptive sampling: theoretical results and a practical algorithm
Computational Optimization and Applications·2026Open Access
A line search framework with restarting for noisy optimization problems
Computational Optimization and Applications·2025
A line search framework with restarting for noisy optimization problems
arXiv (Cornell University)·2025Open Access
Retrospective Approximation Sequential Quadratic Programming for Stochastic Optimization with General Deterministic Nonlinear Constraints
arXiv (Cornell University)·2025Open Access
A flexible gradient tracking algorithmic framework for decentralized optimization
Computational Optimization and Applications·2025
A Sequential Quadratic Programming Method With High-Probability Complexity Bounds for Nonlinear Equality-Constrained Stochastic Optimization
SIAM Journal on Optimization·2025· 3 cited
Collaborative and Distributed Bayesian Optimization via Consensus
IEEE Transactions on Automation Science and Engineering·2025· 3 cited
Scalable Accelerated Materials Discovery of Sustainable Polysaccharide-Based Hydrogels by Autonomous Experimentation and Collaborative Learning
ACS Applied Materials & Interfaces·2024· 1 citedOpen Access
Adaptive Consensus: A Network Pruning Approach for Decentralized Optimization
SIAM Journal on Optimization·2024· 2 cited
Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm
arXiv (Cornell University)·2024Open Access
Balancing Communication and Computation in Gradient Tracking Algorithms for Decentralized Optimization
Journal of Optimization Theory and Applications·2024· 4 cited
Gradient Descent in the Absence of Global Lipschitz Continuity of the Gradients
SIAM Journal on Mathematics of Data Science·2024· 4 citedOpen Access
Modified Line Search Sequential Quadratic Methods for Equality-Constrained Optimization with Unified Global and Local Convergence Guarantees
arXiv (Cornell University)·2024Open Access
Second-order Information Promotes Mini-Batch Robustness in Variance-Reduced Gradients
arXiv (Cornell University)·2024Open Access
A Flexible Gradient Tracking Algorithmic Framework for Decentralized Optimization
arXiv (Cornell University)·2023Open Access
Non-Uniform Smoothness for Gradient Descent
arXiv (Cornell University)·2023Open Access
A Stochastic Sequential Quadratic Optimization Algorithm for Nonlinear-Equality-Constrained Optimization with Rank-Deficient Jacobians
Mathematics of Operations Research·2023· 12 cited
Adaptive Consensus: A network pruning approach for decentralized optimization
arXiv (Cornell University)·2023Open Access
First- and second-order high probability complexity bounds for trust-region methods with noisy oracles
Mathematical Programming·2023· 21 cited
Collaborative and Distributed Bayesian Optimization via Consensus: Showcasing the Power of Collaboration for Optimal Design
arXiv (Cornell University)·2023· 2 citedOpen Access
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Frequent Co-authors

Raghu Bollapragada(11), Martin Takáč(10), Liyuan Cao(7), Katya Scheinberg(7), Ermin Wei(6), Frank E. Curtis(5), Baoyu Zhou(5), Majid Jahani(5), Daniel P. Robinson(4), Shagun Gupta(4), Nitish Shirish Keskar(3), Krzysztof Choromański(3), Jorge Nocedal(3), Xubo Yue(3), Raed Al Kontar(3), Mohammadreza Nazari(3), Charikleia Iakovidou(2), Michael O’Neill(2), Zheng Shi(2), Nur Sila Gulgec(2)