Search Results for author: Minsung Hyun

Found 6 papers, 3 papers with code

Interpolation-based semi-supervised learning for object detection

1 code implementation CVPR 2021 Jisoo Jeong, Vikas Verma, Minsung Hyun, Juho Kannala, Nojun Kwak

Despite the data labeling cost for the object detection tasks being substantially more than that of the classification tasks, semi-supervised learning methods for object detection have not been studied much.

object-detection Object Detection

Class-Imbalanced Semi-Supervised Learning

1 code implementation17 Feb 2020 Minsung Hyun, Jisoo Jeong, Nojun Kwak

First, we analyze existing SSL methods in imbalanced environments and examine how the class imbalance affects SSL methods.

Feature Fusion for Online Mutual Knowledge Distillation

1 code implementation19 Apr 2019 Jangho Kim, Minsung Hyun, Inseop Chung, Nojun Kwak

We propose a learning framework named Feature Fusion Learning (FFL) that efficiently trains a powerful classifier through a fusion module which combines the feature maps generated from parallel neural networks.

Knowledge Distillation

Disentangling Options with Hellinger Distance Regularizer

no code implementations15 Apr 2019 Minsung Hyun, Junyoung Choi, Nojun Kwak

In reinforcement learning (RL), temporal abstraction still remains as an important and unsolved problem.

reinforcement-learning Reinforcement Learning (RL)

Task-oriented Design through Deep Reinforcement Learning

no code implementations13 Mar 2019 Junyoung Choi, Minsung Hyun, Nojun Kwak

We propose a new low-cost machine-learning-based methodology which assists designers in reducing the gap between the problem and the solution in the design process.

BIG-bench Machine Learning reinforcement-learning +1

Towards Governing Agent's Efficacy: Action-Conditional $β$-VAE for Deep Transparent Reinforcement Learning

no code implementations11 Nov 2018 John Yang, Gyujeong Lee, Minsung Hyun, Simyung Chang, Nojun Kwak

We tackle the blackbox issue of deep neural networks in the settings of reinforcement learning (RL) where neural agents learn towards maximizing reward gains in an uncontrollable way.

reinforcement-learning Reinforcement Learning (RL) +1

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