83 citations · 545 across the 36 of their papers we have counts for
38 papers
Novelty Detection Via Blurring
Sungik Choi, Sae-Young Chung
Conventional out-of-distribution (OOD) detection schemes based on variational autoencoder or Random Network Distillation (RND) have been observed to assign lower uncertainty to the…
Robust Training with Ensemble Consensus
Jisoo Lee, Sae-Young Chung
Since deep neural networks are over-parameterized, they can memorize noisy examples. We address such a memorization issue in the presence of label noise. From the fact that deep ne…
Bayesian Approach with Extended Support Estimation for Sparse Regression
Kyung-Su Kim, Sae-Young Chung
A greedy algorithm called Bayesian multiple matching pursuit (BMMP) is proposed to estimate a sparse signal vector and its support given linear measurements. Unlike the maximum…
Fourier Phase Retrieval with Extended Support Estimation via Deep Neural Network
Kyung-Su Kim, Sae-Young Chung
We consider the problem of sparse phase retrieval from Fourier transform magnitudes to recover the -sparse signal vector and its support . We exploit extended suppo…
Tree Search Network for Sparse Regression
Kyung-Su Kim, Sae-Young Chung
We consider the classical sparse regression problem of recovering a sparse signal given a measurement vector . We propose a tree search algorithm driven by the de…
Sample-Efficient Deep Reinforcement Learning via Episodic Backward Update
Su Young Lee, Sungik Choi, Sae-Young Chung
We propose Episodic Backward Update (EBU) - a novel deep reinforcement learning algorithm with a direct value propagation. In contrast to the conventional use of the experience rep…