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20182020
most citedLinear interpolation gives better gradients than Gaussian smoothing in derivative-free optimization

7 citations · 15 across the 4 of their papers we have counts for

collaborators

10 papers

math.OC20206 cited

Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization

Albert Berahas, Frank E. Curtis, Daniel P. Robinson +1

Sequential quadratic optimization algorithms are proposed for solving smooth nonlinear optimization problems with equality constraints. The main focus is an algorithm proposed for…

math.OC20201 cited

SONIA: A Symmetric Blockwise Truncated Optimization Algorithm

Majid Jahani, Mohammadreza Nazari, Rachael Tappenden +2

This work presents a new algorithm for empirical risk minimization. The algorithm bridges the gap between first- and second-order methods by computing a search direction that uses…

stat.ML20201 cited

Finite Difference Neural Networks: Fast Prediction of Partial Differential Equations

Zheng Shi, Nur Sila Gulgec, Albert S. Berahas +2

Discovering the underlying behavior of complex systems is an important topic in many science and engineering disciplines. In this paper, we propose a novel neural network framework…

math.OC2019

Global Convergence Rate Analysis of a Generic Line Search Algorithm with Noise

Albert S. Berahas, Liyuan Cao, Katya Scheinberg

In this paper, we develop convergence analysis of a modified line search method for objective functions whose value is computed with noise and whose gradient estimates are inexact…

math.OC20197 cited

Linear interpolation gives better gradients than Gaussian smoothing in derivative-free optimization

Albert S Berahas, Liyuan Cao, Krzysztof Choromanski +1

In this paper, we consider derivative free optimization problems, where the objective function is smooth but is computed with some amount of noise, the function evaluations are exp…

math.OC2019

Scaling Up Quasi-Newton Algorithms: Communication Efficient Distributed SR1

Majid Jahani, Mohammadreza Nazari, Sergey Rusakov +2

In this paper, we present a scalable distributed implementation of the Sampled Limited-memory Symmetric Rank-1 (S-LSR1) algorithm. First, we show that a naive distributed implement…