Showing items 1 - 20 of 20

Your selections:

A New Look and Convergence Rate of Federated Multitask Learning With Laplacian Regularization

Dynamic V2I/V2V Cooperative Scheme for Connectivity and Throughput Enhancement

Energy-Efficient Massive MIMO for Federated Learning: Transmission Designs and Resource Allocations

Scheduling and Power Control for Connectivity Enhancement in Multi-Hop I2V/V2V Networks

Constraint Reduction Reformulations for Projection Algorithms with Applications to Wavelet Construction

Energy-Efficient Massive MIMO for Serving Multiple Federated Learning Groups

Straggler Effect Mitigation for Federated Learning in Cell-Free Massive MIMO

A Joint Scheduling and Power Control Scheme for Hybrid I2V/V2V Networks

Energy-efficient full-duplex enabled cloud radio access networks

A Lyapunov-type approach to convergence of the Douglas-Rachford algorithm for a nonconvex setting

Adaptive Douglas-Rachford splitting algorithm for the sum of two operators

Computing the resolvent of the sum of operators with application to best approximation problems

Linear convergence of projection algorithms

The Douglas-Rachford algorithm for a hyperplane and a doubleton

Union averaged operators with applications to proximal algorithms for min-convex functions

Energy efficiency maximization for downlink cloud radio access networks with data sharing and data compression

Energy-efficient design for downlink cloud radio access networks

Linear convergence of the generalized Douglas-Rachford algorithm for feasibility problems

Regularizing with Bregman--Moreau envelopes

On Slater’s condition and finite convergence of the Douglas–Rachford algorithm for solving convex feasibility problems in Euclidean spaces

  • 1
  • Disclaimer
  • Privacy
  • Copyright
  • Contact
  • Deposit