What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Algebra
- Algorithm
Shuzhong Zhang mainly investigates Mathematical optimization, Quadratic programming, Semidefinite programming, Combinatorics and Quadratically constrained quadratic program.
His research integrates issues of Computational complexity theory and Convex optimization in his study of Mathematical optimization.
His research in Quadratic programming intersects with topics in Quadratic equation, Quadratic function, Approximation algorithm, Relaxation and Trust region.
In his study, which falls under the umbrella issue of Relaxation, Beamforming and MIMO is strongly linked to Optimization problem.
His study in Semidefinite programming is interdisciplinary in nature, drawing from both Second-order cone programming, Nonlinear programming, Time complexity, Applied mathematics and Linear programming.
His Combinatorics research integrates issues from Positive-definite matrix, Bounded function and Convex set.
His most cited work include:
- Semidefinite Relaxation of Quadratic Optimization Problems (1824 citations)
- Dynamic Spectrum Management: Complexity and Duality (731 citations)
- Internet and Network Economics (311 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Mathematical optimization, Applied mathematics, Semidefinite programming, Convex optimization and Combinatorics.
His research investigates the connection between Mathematical optimization and topics such as Algorithm that intersect with problems in Numerical analysis.
His study on Applied mathematics also encompasses disciplines like
- Curvilinear coordinates most often made with reference to Tensor,
- Matrix which intersects with area such as Robust optimization.
His studies deal with areas such as Path following, Second-order cone programming, Quadratic programming, Semidefinite embedding and Bounded function as well as Semidefinite programming.
Shuzhong Zhang has included themes like Quadratic equation, Quadratic function, Approximation algorithm and Relaxation in his Quadratic programming study.
The study incorporates disciplines such as Rate of convergence, Convex function and Convexity in addition to Convex optimization.
He most often published in these fields:
- Mathematical optimization (38.94%)
- Applied mathematics (22.11%)
- Semidefinite programming (19.47%)
What were the highlights of his more recent work (between 2017-2021)?
- Applied mathematics (22.11%)
- Ambiguity (3.96%)
- Convex optimization (18.48%)
In recent papers he was focusing on the following fields of study:
Shuzhong Zhang mostly deals with Applied mathematics, Ambiguity, Convex optimization, Convex function and Mathematical optimization.
His work deals with themes such as Hessian matrix, Tensor, Order, Regularization and Optimization problem, which intersect with Applied mathematics.
His research integrates issues of Acceleration, Product and Duality in his study of Tensor.
His research on Convex optimization concerns the broader Regular polygon.
His Convex function research includes elements of Combinatorics, Strongly monotone, Convexity, Variational inequality and Upper and lower bounds.
His works in Linear programming and Interior point method are all subjects of inquiry into Mathematical optimization.
Between 2017 and 2021, his most popular works were:
- Highly accurate model for prediction of lung nodule malignancy with CT scans. (77 citations)
- On the Information-Adaptive Variants of the ADMM: An Iteration Complexity Perspective (45 citations)
- Structured nonconvex and nonsmooth optimization: algorithms and iteration complexity analysis (44 citations)
In his most recent research, the most cited papers focused on:
- Algebra
- Artificial intelligence
- Algorithm
Shuzhong Zhang focuses on Convex function, Convex optimization, Mathematical optimization, Applied mathematics and Regular polygon.
The Convex function study combines topics in areas such as Upper and lower bounds, Lipschitz continuity and Combinatorics.
His Combinatorics study integrates concerns from other disciplines, such as Strongly monotone, Saddle point and Type.
Shuzhong Zhang has researched Mathematical optimization in several fields, including Computational complexity theory, Rate of convergence, Stochastic approximation and Convexity.
His biological study spans a wide range of topics, including Function and Global iteration.
His Regular polygon research is multidisciplinary, relying on both Regularization, Hessian matrix and Unconstrained optimization.
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