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20212026
most citedA Field Test of Bandit Algorithms for Recommendations: Understanding the Validity of Assumptions on Human Preferences in Multi-armed Bandits

3 citations · 3 across the 5 of their papers we have counts for

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5 papers

math.OC2026

From Majorization to Scaling: Advancing Convex Relaxations of Maximum Entropy Sampling Problem

Lingqing Shen, Fatma Kılınç-Karzan

In this paper, we study the maximum entropy sampling problem (MESP) and its variants. MESP seeks to identify a small subset of variables that maximizes the determinant of a covaria…

math.OC2025

Convergence, Duality and Well-Posedness in Convex Bilevel Optimization

Khanh-Hung Giang-Tran, Nam Ho-Nguyen, Fatma Kılınç-Karzan +1

We consider the convex bilevel optimization problem, also known as simple bilevel programming. There are two challenges in solving convex bilevel optimization problems. Firstly, st…

math.OC2024

On the strength of Burer's lifted convex relaxation to quadratic programming with ball constraints

Fatma Kılınç-Karzan, Shengding Sun

We study quadratic programs with ball constraints, and the strength of a lifted convex relaxation for it recently proposed by Burer (2024). Burer shows this relaxation is exact…

cs.IR20233 cited

A Field Test of Bandit Algorithms for Recommendations: Understanding the Validity of Assumptions on Human Preferences in Multi-armed Bandits

Liu Leqi, Giulio Zhou, Fatma Kılınç-Karzan +2

Personalized recommender systems suffuse modern life, shaping what media we read and what products we consume. Algorithms powering such systems tend to consist of supervised learni…

math.OC2021

Exactness in SDP relaxations of QCQPs: Theory and applications

Fatma Kılınç-Karzan, Alex L. Wang

Quadratically constrained quadratic programs (QCQPs) are a fundamental class of optimization problems. In a QCQP, we are asked to minimize a (possibly nonconvex) quadratic function…