New Environment Adaptation with Few Shots for OFDM Receiver and mmWave
Beamforming

New Environment Adaptation with Few Shots for OFDM Receiver and mmWave Beamforming

18 October 2023

Geoffrey Ye Li

ArXiv (abs)PDF HTML

Papers citing "New Environment Adaptation with Few Shots for OFDM Receiver and mmWave Beamforming"

6 / 6 papers shown

Title
BADM: Batch ADMM for Deep Learning Ouya Wang Shenglong Zhou Geoffrey Ye Li ODL 107 1 0 30 Jun 2024
A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunities Yisheng Song Ting-Yuan Wang S. Mondal J. P. Sahoo SLR 118 375 0 13 May 2022
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Colin Raffel Noam M. Shazeer Adam Roberts Katherine Lee Sharan Narang Michael Matena Yanqi Zhou Wei Li Peter J. Liu AIMat 456 20,298 0 23 Oct 2019
Meta-Transfer Learning for Few-Shot Learning Qianru Sun Yaoyao Liu Tat-Seng Chua Bernt Schiele 204 1,071 0 06 Dec 2018
Model-Driven Deep Learning for Physical Layer Communications Hengtao He Shi Jin Chao-Kai Wen Fei Gao Geoffrey Ye Li Zongben Xu AI4CE 60 375 0 17 Sep 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 825 11,937 0 09 Mar 2017