Negar Soheili
Negar Soheili
Assistant Professor of Business Analytics
Verified email at uic.edu - Homepage
Title
Cited by
Cited by
Year
A smooth perceptron algorithm
JP Negar Soheili
SIAM Journal on Optimization 22, 728--737, 2012
252012
On the von Neumann and Frank--Wolfe algorithms with away steps
J Pena, D Rodríguez, N Soheili
SIAM Journal on Optimization 26 (1), 499-512, 2016
222016
A level-set method for convex optimization with a feasible solution path
Q Lin, S Nadarajah, N Soheili
SIAM Journal on Optimization 28 (4), 3290-3311, 2018
212018
Solving conic systems via projection and rescaling
J Pena, N Soheili
Mathematical Programming 166 (1), 87-111, 2017
202017
A deterministic rescaled perceptron algorithm
NS J Pena
Math. Programming, 2015
182015
A primal-dual smooth perceptron-von Neumann algorithm
JP Negar Soheili
Discrete Geometry and Optimization. Springer, Fields Institute …, 2013
13*2013
Revisiting approximate linear programming: Constraint-violation learning with applications to inventory control and energy storage
Q Lin, S Nadarajah, N Soheili
Management Science 66 (4), 1544-1562, 2020
62020
A condition-based algorithm for solving polyhedral feasibility problems
JP Negar Soheili
Journal o Complexity 30, 673--682, 2014
52014
A data efficient and feasible level set method for stochastic convex optimization with expectation constraints
Q Lin, S Nadarajah, N Soheili, T Yang
Journal of machine learning research, 2020
42020
Some preconditioners for systems of linear inequalities
J Pena, V Roshchina, N Soheili
Optimization Letters 8 (7), 2145-2152, 2014
42014
Computational performance of a projection and rescaling algorithm
J Pena, N Soheili
Optimization Methods and Software, 1-18, 2019
32019
First-Order Methods for Convex Constrained Optimization under Error Bound Conditions with Unknown Growth Parameters
Q Lin, R Ma, S Nadarajah, N Soheili
arXiv preprint arXiv:2010.15267, 2020
12020
Projection and rescaling algorithm for finding most interior solutions to polyhedral conic systems
J Pena, N Soheili
arXiv preprint arXiv:2003.08911, 2020
2020
Self-guided Approximate Linear Programs
P Pakiman, S Nadarajah, N Soheili, Q Lin
Available at SSRN 3512665, 2020
2020
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Articles 1–14