Yunier Bello Cruz

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Associate Professor

Northern Illinois University

United States

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About

Yunier Bello Cruz is an Associate Professor at Northern Illinois University, USA. His research primarily focuses on optimization methods and convex analysis, with recent publications addressing topics such as projection equations, proximal gradient methods, and convex feasibility problems. He is actively involved in exploring convergence properties and algorithmic approaches in the field of mathematical optimization.

Recent Grants

Grant: Close

Design and Analysis of Algorithms for Structured Optimization

Open Date: 2023-06-01

Close Date: 2026-06-01

Grant: Close

Second-Order Variational Analysis in Structured Optimization and Algorithms with Applications

Open Date: 2018-09-01

Close Date: 2021-08-01

Grant: Close

CNPq 303492/2013-9

Open Date: 2014-03-01

Close Date: 2017-02-01

Grant: Close

CNPq 474160/2013-0

Open Date: 2013-11-01

Close Date: 2016-12-01

Articles (13)

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2025

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2025

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2024

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2023

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2023

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2023

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2023

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2023

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2022

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2022

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2022

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2021

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2021

Collaborators (1)

Guoyin Li

University of New South Wales

AUSTRALIA

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Yunier Bello Cruz

Research Interests

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About

Recent Grants

Articles (13)

A semi-smooth Newton method for general projection equations applied to the nearest correlation matrix problem

A Relative Inexact Proximal Gradient Method with an Explicit Linesearch

A Finitely Convergent Circumcenter Method for the Convex Feasibility Problem

A successive centralized circumcentered-reflection method for the convex feasibility problem

On the centralization of the circumcentered-reflection method

Circumcentric directions of cones

On the weak and strong convergence of modified forward-backward-half-forward splitting methods

On FISTA with a relative error rule

Circumcentering approximate reflections for solving the convex feasibility problem

Quadratic Growth Conditions and Uniqueness of Optimal Solution to Lasso

A proximal gradient splitting method for solving convex vector optimization problems

The circumcentered-reflection method achieves better rates than alternating projections

On the Linear Convergence of Forward–Backward Splitting Method: Part I—Convergence Analysis

Collaborators (1)

Guoyin Li

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