activity
20182022
most citedSRM : A Style-based Recalibration Module for Convolutional Neural Networks

42 citations · 43 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2022

Improving Multi-fidelity Optimization with a Recurring Learning Rate for Hyperparameter Tuning

HyunJae Lee, Gihyeon Lee, Junhwan Kim +3

Despite the evolution of Convolutional Neural Networks (CNNs), their performance is surprisingly dependent on the choice of hyperparameters. However, it remains challenging to effi…

cs.CL20211 cited

KoreALBERT: Pretraining a Lite BERT Model for Korean Language Understanding

Hyunjae Lee, Jaewoong Yoon, Bonggyu Hwang +3

A Lite BERT (ALBERT) has been introduced to scale up deep bidirectional representation learning for natural languages. Due to the lack of pretrained ALBERT models for Korean langua…

cs.CV2019

Reducing Domain Gap by Reducing Style Bias

Hyeonseob Nam, HyunJae Lee, Jongchan Park +2

Convolutional Neural Networks (CNNs) often fail to maintain their performance when they confront new test domains, which is known as the problem of domain shift. Recent studies sug…

cs.CV201942 cited

SRM : A Style-based Recalibration Module for Convolutional Neural Networks

HyunJae Lee, Hyo-Eun Kim, Hyeonseob Nam

Following the advance of style transfer with Convolutional Neural Networks (CNNs), the role of styles in CNNs has drawn growing attention from a broader perspective. In this paper,…

cs.AI2018

Clear the Fog: Combat Value Assessment in Incomplete Information Games with Convolutional Encoder-Decoders

Hyungu Kahng, Yonghyun Jeong, Yoon Sang Cho +12

StarCraft, one of the most popular real-time strategy games, is a compelling environment for artificial intelligence research for both micro-level unit control and macro-level stra…