no code implementations • 29 Mar 2023 • Hong-Jun Choi, Dongbin Na, Kyungjin Cho, Byunguk Bae, Seo Taek Kong, Hyunjoon An
This study presents a novel approach to bone age assessment (BAA) using a multi-view, multi-task classification model based on the Sauvegrain method.
no code implementations • 14 Feb 2023 • Seo Taek Kong, Saptarshi Mandal, Dimitrios Katselis, R. Srikant
After separating tasks by type, any Dawid-Skene algorithm (i. e., any algorithm designed for the Dawid-Skene model) can be applied independently to each type to infer the truth values.
1 code implementation • 26 Dec 2022 • Jaeyoung Kim, Seo Taek Kong, Dongbin Na, Kyu-Hwan Jung
We first deduce that OOD images are perceived by a deep neural network to be semantically similar to in-distribution samples when they share a common background, as deep networks are observed to incorrectly classify such images with high confidence.
Out-of-Distribution Detection Out of Distribution (OOD) Detection
no code implementations • 8 Apr 2021 • Seo Taek Kong, Soomin Jeon, Dongbin Na, Jaewon Lee, Hong-Seok Lee, Kyu-Hwan Jung
Although unlabeled data is readily available in pool-based AL, AL algorithms are usually evaluated by measuring the increase in supervised learning (SL) performance at consecutive acquisition steps.
no code implementations • 1 Jan 2021 • Seo Taek Kong, Soomin Jeon, Jaewon Lee, Hong-Seok Lee, Kyu-Hwan Jung
We name this AL scheme convergence rate control (CRC), and our experiments show that a deep neural network trained using a combination of CRC and a recently proposed SSL algorithm can quickly achieve high performance using far less labeled samples than SL.
no code implementations • 25 Jan 2019 • Harsh Gupta, Seo Taek Kong, R. Srikant, Weina Wang
In this paper, we show that a simple modification to Boltzmann exploration, motivated by a variation of the standard doubling trick, achieves $O(K\log^{1+\alpha} T)$ regret for a stochastic MAB problem with $K$ arms, where $\alpha>0$ is a parameter of the algorithm.