10 citations · 15 across the 6 of their papers we have counts for
6 papers · 1 filter
AID-Purifier: A Light Auxiliary Network for Boosting Adversarial Defense
Duhun Hwang, Eunjung Lee, Wonjong Rhee
We propose an AID-purifier that can boost the robustness of adversarially-trained networks by purifying their inputs. AID-purifier is an auxiliary network that works as an add-on t…
Short-term Traffic Prediction with Deep Neural Networks: A Survey
Kyungeun Lee, Moonjung Eo, Euna Jung +2
In modern transportation systems, an enormous amount of traffic data is generated every day. This has led to rapid progress in short-term traffic prediction (STTP), in which deep l…
DEEP-BO for Hyperparameter Optimization of Deep Networks
Hyunghun Cho, Yongjin Kim, Eunjung Lee +3
The performance of deep neural networks (DNN) is very sensitive to the particular choice of hyper-parameters. To make it worse, the shape of the learning curve can be significantly…
Subtask Gated Networks for Non-Intrusive Load Monitoring
Changho Shin, Sunghwan Joo, Jaeryun Yim +3
Non-intrusive load monitoring (NILM), also known as energy disaggregation, is a blind source separation problem where a household's aggregate electricity consumption is broken down…
Statistical Characteristics of Deep Representations: An Empirical Investigation
Daeyoung Choi, Kyungeun Lee, Duhun Hwang +1
In this study, the effects of eight representation regularization methods are investigated, including two newly developed rank regularizers (RR). The investigation shows that the s…
Utilizing Class Information for Deep Network Representation Shaping
Daeyoung Choi, Wonjong Rhee
Statistical characteristics of deep network representations, such as sparsity and correlation, are known to be relevant to the performance and interpretability of deep learning. Wh…