2 citations · 6 across the 16 of their papers we have counts for
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cs.LG2019★ 1 cited
Adaptive Regularization via Residual Smoothing in Deep Learning Optimization
Junghee Cho, Junseok Kwon, Byung-Woo Hong
We present an adaptive regularization algorithm that can be effectively applied to the optimization problem in deep learning framework. Our regularization algorithm aims to take in…
cs.LG2019
Adaptive Weight Decay for Deep Neural Networks
Kensuke Nakamura, Byung-Woo Hong
Regularization in the optimization of deep neural networks is often critical to avoid undesirable over-fitting leading to better generalization of model. One of the most popular re…
cs.CV2019
Bilateral Cyclic Constraint and Adaptive Regularization for Unsupervised Monocular Depth Prediction
Alex Wong, Byung-Woo Hong, Stefano Soatto
Supervised learning methods to infer (hypothesize) depth of a scene from a single image require costly per-pixel ground-truth. We follow a geometric approach that exploits abundant…