122 citations · 289 across the 9 of their papers we have counts for
10 papers
Task-Adaptive Pseudo Labeling for Transductive Meta-Learning
Sanghyuk Lee, Seunghyun Lee, Byung Cheol Song
Meta-learning performs adaptation through a limited amount of support set, which may cause a sample bias problem. To solve this problem, transductive meta-learning is getting more…
Latent Conjunctive Bayesian Network: Unify Attribute Hierarchy and Bayesian Network for Cognitive Diagnosis
Seunghyun Lee, Yuqi Gu
Cognitive diagnostic assessment aims to measure specific knowledge structures in students. To model data arising from such assessments, cognitive diagnostic models with discrete la…
CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly Localization
Sungwook Lee, Seunghyun Lee, Byung Cheol Song
For a long time, anomaly localization has been widely used in industries. Previous studies focused on approximating the distribution of normal features without adaptation to a targ…
Ensemble Knowledge Guided Sub-network Search and Fine-tuning for Filter Pruning
Seunghyun Lee, Byung Cheol Song
Conventional NAS-based pruning algorithms aim to find the sub-network with the best validation performance. However, validation performance does not successfully represent test per…
Vision Transformer for Small-Size Datasets
Seung Hoon Lee, Seunghyun Lee, Byung Cheol Song
Recently, the Vision Transformer (ViT), which applied the transformer structure to the image classification task, has outperformed convolutional neural networks. However, the high…
Contextual Gradient Scaling for Few-Shot Learning
Sanghyuk Lee, Seunghyun Lee, Byung Cheol Song
Model-agnostic meta-learning (MAML) is a well-known optimization-based meta-learning algorithm that works well in various computer vision tasks, e.g., few-shot classification. MAML…
Graph-based Knowledge Distillation by Multi-head Attention Network
Seunghyun Lee, Byung Cheol Song
Knowledge distillation (KD) is a technique to derive optimal performance from a small student network (SN) by distilling knowledge of a large teacher network (TN) and transferring…
Self-supervised Knowledge Distillation Using Singular Value Decomposition
Seung Hyun Lee, Dae Ha Kim, Byung Cheol Song
To solve deep neural network (DNN)'s huge training dataset and its high computation issue, so-called teacher-student (T-S) DNN which transfers the knowledge of T-DNN to S-DNN has b…
Evidence of electronic cloaking from chiral electron transport in bilayer graphene nanostructures
Kyunghoon Lee, Seunghyun Lee, Yun Suk Eo +2
The coupling of charge carrier motion and pseudospin via chirality for massless Dirac fermions in monolayer graphene has generated dramatic consequences, such as the unusual quantu…
Flexible and Transparent All-Graphene Circuits for Quaternary Digital Modulations
Seunghyun Lee, Kyunghoon Lee, Chang-Hua Liu +2
In modern communication system, modulation is a key function that embeds the baseband signal (information) into a carrier wave so that it can be successfully broadcasted through a…