10 citations · 15 across the 6 of their papers we have counts for
5 papers · 1 filter
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…
Restructuring Batch Normalization to Accelerate CNN Training
Wonkyung Jung, Daejin Jung, and Byeongho Kim +3
Batch Normalization (BN) has become a core design block of modern Convolutional Neural Networks (CNNs). A typical modern CNN has a large number of BN layers in its lean and deep ar…
Partitioning Compute Units in CNN Acceleration for Statistical Memory Traffic Shaping
Daejin Jung, Sunjung Lee, Wonjong Rhee +1
The design complexity of CNNs has been steadily increasing to improve accuracy. To cope with the massive amount of computation needed for such complex CNNs, the latest solutions ut…