3 citations · 6 across the 4 of their papers we have counts for
4 papers
Active Learning for Finely-Categorized Image-Text Retrieval by Selecting Hard Negative Unpaired Samples
Dae Ung Jo, Kyuewang Lee, JaeHo Chung +1
Securing a sufficient amount of paired data is important to train an image-text retrieval (ITR) model, but collecting paired data is very expensive. To address this issue, in this…
Confidence-Based Feature Imputation for Graphs with Partially Known Features
Daeho Um, Jiwoong Park, Seulki Park +1
This paper investigates a missing feature imputation problem for graph learning tasks. Several methods have previously addressed learning tasks on graphs with missing features. How…
Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning
Jiwoong Park, Minsik Lee, Hyung Jin Chang +2
We propose a symmetric graph convolutional autoencoder which produces a low-dimensional latent representation from a graph. In contrast to the existing graph autoencoders with asym…
Neuro-Optimization: Learning Objective Functions Using Neural Networks
Younghan Jeon, Minsik Lee, Jin Young Choi
Mathematical optimization is widely used in various research fields. With a carefully-designed objective function, mathematical optimization can be quite helpful in solving many pr…