What is he best known for?
The fields of study he is best known for:
- Computer network
- Algorithm
- Mathematical optimization
Zhi-Quan Luo mainly investigates Mathematical optimization, Algorithm, Control theory, Convex optimization and Wireless sensor network.
His Mathematical optimization research is multidisciplinary, incorporating perspectives in Convergence, Beamforming and Robustness.
His biological study spans a wide range of topics, including Ambiguity function, Signal, Radar and Affine transformation.
His studies in Control theory integrate themes in fields like Time complexity, MIMO, Quadrature amplitude modulation and Topology.
The various areas that Zhi-Quan Luo examines in his Convex optimization study include Posynomial and Optimization problem.
His research in Wireless sensor network intersects with topics in Quantization, Computer engineering, Network topology, Estimator and Sensor array.
His most cited work include:
- Semidefinite Relaxation of Quadratic Optimization Problems (1824 citations)
- Mathematical Programs with Equilibrium Constraints (1441 citations)
- Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem (1135 citations)
What are the main themes of his work throughout his whole career to date?
Zhi-Quan Luo spends much of his time researching Mathematical optimization, Algorithm, Convex optimization, Beamforming and Control theory.
His work in Mathematical optimization tackles topics such as Computational complexity theory which are related to areas like Time complexity.
His Algorithm study combines topics in areas such as Multiuser detection, Detector, Signal-to-noise ratio and Sensor fusion.
His Convex optimization research is multidisciplinary, incorporating elements of Convex function and Semidefinite programming.
His work is dedicated to discovering how Beamforming, MIMO are connected with Base station and other disciplines.
His Control theory research includes elements of Wireless sensor network and Communication channel.
He most often published in these fields:
- Mathematical optimization (38.84%)
- Algorithm (24.89%)
- Convex optimization (14.81%)
What were the highlights of his more recent work (between 2015-2021)?
- Algorithm (24.89%)
- Mathematical optimization (38.84%)
- Beamforming (12.88%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Algorithm, Mathematical optimization, Beamforming, Distributed computing and Applied mathematics.
The concepts of his Algorithm study are interwoven with issues in MIMO and Coordinate system.
His Mathematical optimization research incorporates elements of Function, Convergence, Telecommunications link and Convex optimization.
His Convex optimization research incorporates themes from Point and Sparse matrix.
His research integrates issues of Iterative method, Speech recognition, Robustness and Minimum-variance unbiased estimator in his study of Beamforming.
His work carried out in the field of Distributed computing brings together such families of science as Telecommunications network, Node, Subnetwork and Efficient energy use.
Between 2015 and 2021, his most popular works were:
- Convergence Analysis of Alternating Direction Method of Multipliers for a Family of Nonconvex Problems (464 citations)
- On the linear convergence of the alternating direction method of multipliers (422 citations)
- A Unified Algorithmic Framework for Block-Structured Optimization Involving Big Data: With applications in machine learning and signal processing (216 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Statistics
- Algorithm
His main research concerns Mathematical optimization, Algorithm, Convergence, Applied mathematics and Coordinate descent.
In the subject of general Mathematical optimization, his work in Slack variable is often linked to Block, thereby combining diverse domains of study.
His study in Algorithm is interdisciplinary in nature, drawing from both MIMO, Initialization and Norm.
His study focuses on the intersection of MIMO and fields such as Minimum mean square error with connections in the field of Beamforming.
The study incorporates disciplines such as Iterated function, Selection, Function, Variable and Augmented Lagrangian method in addition to Convergence.
His work deals with themes such as Discrete mathematics, Sublinear function, Combinatorics, Minification and Gradient descent, which intersect with Coordinate descent.
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