2 papers
cs.LG2021
Mitigating Memorization in Sample Selection for Learning with Noisy Labels
Kyeongbo Kong, Junggi Lee, Youngchul Kwak +3
Because deep learning is vulnerable to noisy labels, sample selection techniques, which train networks with only clean labeled data, have attracted a great attention. However, if t…
eess.SP2020
Knowledge Distillation-aided End-to-End Learning for Linear Precoding in Multiuser MIMO Downlink Systems with Finite-Rate Feedback
Kyeongbo Kong, Woo-Jin Song, Moonsik Min
We propose a deep learning-based channel estimation, quantization, feedback, and precoding method for downlink multiuser multiple-input and multiple-output systems. In the proposed…