no code implementations • 31 May 2022 • Kisung Moon, Sunyoung Kwon
Self-supervised learning (SSL) is a method that learns the data representation by utilizing supervision inherent in the data.
1 code implementation • 1 Mar 2021 • Dasol Hwang, Jinyoung Park, Sunyoung Kwon, Kyung-Min Kim, Jung-Woo Ha, Hyunwoo J. Kim
Our method is learning to learn a primary task with various auxiliary tasks to improve generalization performance.
no code implementations • 31 Jan 2021 • Kyung-Wha Park, Jung-Woo Ha, Junghoon Lee, Sunyoung Kwon, Kyung-Min Kim, Byoung-Tak Zhang
Assessing advertisements, specifically on the basis of user preferences and ad quality, is crucial to the marketing industry.
no code implementations • 14 Aug 2020 • Wonyoung Shin, Jung-Woo Ha, Shengzhe Li, Yongwoo Cho, Hoyean Song, Sunyoung Kwon
Label noise is a critical factor that degrades the generalization performance of deep neural networks, thus leading to severe issues in real-world problems.
Ranked #23 on Image Classification on Clothing1M (using extra training data)
1 code implementation • NeurIPS 2020 • Dasol Hwang, Jinyoung Park, Sunyoung Kwon, Kyung-Min Kim, Jung-Woo Ha, Hyunwoo J. Kim
Our proposed method is learning to learn a primary task by predicting meta-paths as auxiliary tasks.
no code implementations • 5 Jul 2020 • Kyuyong Shin, Young-Jin Park, Kyung-Min Kim, Sunyoung Kwon
The key to the success of precise user targeting lies in learning the accurate user and ad representation in the embedding space.
no code implementations • 18 May 2020 • Kyuyong Shin, Wonyoung Shin, Jung-Woo Ha, Sunyoung Kwon
Existing approaches for graph neural networks commonly suffer from the oversmoothing issue, regardless of how neighborhoods are aggregated.
no code implementations • 6 Oct 2019 • Kyung-Wha Park, Junghoon Lee, Sunyoung Kwon, Jung-Woo Ha, Kyung-Min Kim, Byoung-Tak Zhang
Despite crucial influences of image quality, auxiliary information of ad images such as tags and target subjects can also determine image preference.
2 code implementations • 27 Apr 2017 • Sunyoung Kwon, Sungroh Yoon
To guarantee the commutative property for homogeneous interaction, we apply model sharing and hidden representation merging techniques.
no code implementations • 27 Apr 2017 • Ho Bae, Byunghan Lee, Sunyoung Kwon, Sungroh Yoon
We compare our proposed method to various existing methods and biological sequence analysis methods implemented on top of our framework.
1 code implementation • 16 Nov 2015 • Sunyoung Kwon, Gyuwan Kim, Byunghan Lee, Jongsik Chun, Sungroh Yoon, Young-Han Kim
Motivated by the need for fast and accurate classification of unlabeled nucleotide sequences on a large scale, we developed NASCUP, a new classification method that captures statistical structures of nucleotide sequences by compact context-tree models and universal probability from information theory.
Genomics Information Theory Information Theory