Conical averagedness and convergence analysis of fixed point algorithms
We study a conical extension of averaged nonexpansive operators and the role it plays in...
Data Size-Aware Downlink Massive MIMO: A Session-Based Approach
Dynamic V2I/V2V Cooperative Scheme for Connectivity and Throughput Enhancement
Extrapolated Proximal Subgradient Algorithms for Nonconvex and Nonsmooth Fractional Programs
Graph Augmentation Learning
Joint Resource Allocation to Minimize Execution Time of Federated Learning in Cell-Free Massive MIMO
Scheduling and Power Control for Connectivity Enhancement in Multi-Hop I2V/V2V Networks
An adaptive splitting algorithm for the sum of two generalized monotone operators and one cocoercive operator
Splitting algorithms for finding a zero of sum of operators often involve multiple steps which...
Constraint Reduction Reformulations for Projection Algorithms with Applications to Wavelet Construction
We introduce a reformulation technique that converts a many-set feasibility problem into an...
Energy-Efficient Massive MIMO for Serving Multiple Federated Learning Groups
Generalized Bregman Envelopes and Proximity Operators
The generalized Bregman distance
Recently, a new kind of distance has been introduced for the graphs of two point-to-set...
A Joint Scheduling and Power Control Scheme for Hybrid I2V/V2V Networks
In automotive infotainment systems, vehicles using the applications are serviced via continuous...
Cell-Free Massive MIMO for Wireless Federated Learning
This paper proposes a novel scheme for cell-free massive multiple-input multiple-output (CFmMIMO)...
Computing the resolvent of the sum of operators with application to best approximation problems
We propose a flexible approach for computing the resolvent of the sum of weakly monotone...
Energy-efficient full-duplex enabled cloud radio access networks
This paper studies the joint optimization of precoding, transmit power and data rate allocation...
Adaptive Douglas-Rachford Splitting Algorithm for the Sum of Two Operators
The Douglas–Rachford algorithm is a classical and powerful splitting method for minimizing the...
A Lyapunov-type approach to convergence of the Douglas–Rachford algorithm for a nonconvex setting
The Douglas–Rachford projection algorithm is an iterative method used to find a point in the...
Linear convergence of projection algorithms
Projection algorithms are well known for their simplicity and flexibility in solving feasibility...
The Douglas–Rachford algorithm for a hyperplane and a doubleton
The Douglas–Rachford algorithm is a popular algorithm for solving both convex and nonconvex...
Union Averaged Operators with Applications to Proximal Algorithms for Min-Convex Functions
In this paper, we introduce and study a class of structured set-valued operators, which we call...
Energy Efficiency Maximization for Downlink Cloud Radio Access Networks with Data Sharing and Data Compression
This paper aims to maximize the energy efficiency of a downlink cloud radio access network...
Energy-Efficient Design for Downlink Cloud Radio Access Networks
This work aims to maximize the energy efficiency of a downlink cloud radio access network...
Linear convergence of the generalized Douglas–Rachford algorithm for feasibility problems
In this paper, we study the generalized Douglas–Rachford algorithm and its cyclic variants which...
Regularizing with Bregman–Moreau envelopes
Moreau’s seminal paper, introducing what is now called the Moreau envelope and the proximity...
Spectral and energy efficiency maximization for content-centric C-RANs with edge caching
This paper aims to maximize the spectral and energy efficiencies of a content-centric cloud radio...
On the finite convergence of the Douglas-Rachford algorithm for solving (not necessarily convex) feasibility problems in Euclidean spaces
Solving feasibility problems is a central task in mathematics and the applied sciences. One...
Nonconvex bundle method with application to a delamination problem
Delamination is a typical failure mode of composite materials caused by weak bonding. It arises...
On Slater’s condition and finite convergence of the Douglas–Rachford algorithm for solving convex feasibility problems in Euclidean spaces
The Douglas–Rachford algorithm is a classical and very successful method for solving optimization...
Proximal point algorithm, Douglas-Rachford algorithm and alternating projections: A case study
Many iterative methods for solving optimization or feasibility problems have been invented, and...
The Douglas-Rachford algorithm in the affine-convex case
The Douglas-Rachford algorithm is a simple yet effective method for solving convex feasibility...
Bundle method for nonconvex nonsmooth constrained optimization
The paper develops a nonconvex bundle method based on the downshift mechanism and a proximity...
Minimizing memory effects of a system
Given a stable linear time-invariant system with tunable parameters, we present a method to tune...
On Fejér monotone sequences and nonexpansive mappings
The notion of Fejer monotonicity has proven to be a fruitful concept in fixed point theory and...
Parametric Robust Structured Control Design
We present a new approach to parametric robust controller design, where we compute controllers of...
Robust eigenstructure clustering by non-smooth optimisation
We extend classical eigenstructure assignment to more realistic problems, where additional...
Minimizing the memory of a system
Consider a stable linear time-invariant system G(x) with tunable parameters x Rn, which maps...
Optimized eigenstructure assignment
This paper considers the problem of eigenstructure assignment for output feedback control. We...
Simultaneous plant and controller optimization based on non-smooth techniques
We present an approach to simultaneous design optimization of a plant and its controller. This is...