99 citations · 139 across the 4 of their papers we have counts for
6 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…
Clinical Decision Transformer: Intended Treatment Recommendation through Goal Prompting
Seunghyun Lee, Da Young Lee, Sujeong Im +2
With recent achievements in tasks requiring context awareness, foundation models have been adopted to treat large-scale data from electronic health record (EHR) systems. However, p…
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…
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…