61 citations · 158 across the 6 of their papers we have counts for
6 papers
Semi-orthogonal Embedding for Efficient Unsupervised Anomaly Segmentation
Jin-Hwa Kim, Do-Hyeong Kim, Saehoon Yi +1
We present the efficiency of semi-orthogonal embedding for unsupervised anomaly segmentation. The multi-scale features from pre-trained CNNs are recently used for the localized Mah…
Semi-supervised Learning with Deep Generative Models for Asset Failure Prediction
Andre S. Yoon, Taehoon Lee, Yongsub Lim +5
This work presents a novel semi-supervised learning approach for data-driven modeling of asset failures when health status is only partially known in historical data. We combine a…
DNA-Level Splice Junction Prediction using Deep Recurrent Neural Networks
Byunghan Lee, Taehoon Lee, Byunggook Na +1
A eukaryotic gene consists of multiple exons (protein coding regions) and introns (non-coding regions), and a splice junction refers to the boundary between a pair of exon and intr…
Manifold Regularized Deep Neural Networks using Adversarial Examples
Taehoon Lee, Minsuk Choi, Sungroh Yoon
Learning meaningful representations using deep neural networks involves designing efficient training schemes and well-structured networks. Currently, the method of stochastic gradi…
Regularization and Kernelization of the Maximin Correlation Approach
Taehoon Lee, Taesup Moon, Seung Jean Kim +1
Robust classification becomes challenging when each class consists of multiple subclasses. Examples include multi-font optical character recognition and automated protein function…
High-dimensional Fused Lasso Regression using Majorization-Minimization and Parallel Processing
Donghyeon Yu, Joong-Ho Won, Taehoon Lee +2
In this paper, we propose a majorization-minimization (MM) algorithm for high-dimensional fused lasso regression (FLR) suitable for parallelization using graphics processing units…