Search Results for author:
Found 4 papers, 1 papers with code
Federated Learning Using Three-Operator ADMM
We propose FedTOP-ADMM, which generalizes FedADMM and is based on a three-operator ADMM-type technique that exploits a smooth cost function on the edge server to learn a global model parallel to the edge devices.
EVM Mitigation with PAPR and ACLR Constraints in Large-Scale MIMO-OFDM Using TOP-ADMM
Although signal distortion-based peak-to-average power ratio (PAPR) reduction is a feasible candidate for orthogonal frequency division multiplexing (OFDM) to meet standard/regulatory requirements, the error vector magnitude (EVM) stemming from the PAPR reduction has a deleterious impact on the performance of high data-rate achieving multiple-input multiple-output (MIMO) systems.
EVM-Constrained and Mask-Compliant MIMO-OFDM Spectral Precoding
In this paper we propose a novel spectral precoding approach which constrains the EVM while complying with the mask requirements.
Neural Networks for Fashion Image Classification and Visual Search
An image based search algorithm can unleash the true potential of ecommerce by enabling customers to click a picture of an object and search for similar products without the need for typing.
