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math.OC2023
An Inexact Frank-Wolfe Algorithm for Composite Convex Optimization Involving a Self-Concordant Function
Nimita Shinde, Vishnu Narayanan, James Saunderson
In this paper, we consider Frank-Wolfe-based algorithms for composite convex optimization problems with objective involving a logarithmically-homogeneous, self-concordant functions…
math.OC2021
Memory-Efficient Approximation Algorithms for Max-k-Cut and Correlation Clustering
Nimita Shinde, Vishnu Narayanan, James Saunderson
Max-k-Cut and correlation clustering are fundamental graph partitioning problems. For a graph with G=(V,E) with n vertices, the methods with the best approximation guarantees for M…
math.OC2020
Memory-efficient structured convex optimization via extreme point sampling
Nimita Shinde, Vishnu Narayanan, James Saunderson
Memory is a key computational bottleneck when solving large-scale convex optimization problems such as semidefinite programs (SDPs). In this paper, we focus on the regime in which…