78 citations · 103 across the 9 of their papers we have counts for
13 papers
POEM: Polarization of Embeddings for Domain-Invariant Representations
Sang-Yeong Jo, Sung Whan Yoon
Handling out-of-distribution samples is a long-lasting challenge for deep visual models. In particular, domain generalization (DG) is one of the most relevant tasks that aims to tr…
Task-Adaptive Feature Transformer with Semantic Enrichment for Few-Shot Segmentation
Jun Seo, Young-Hyun Park, Sung Whan Yoon +1
Few-shot learning allows machines to classify novel classes using only a few labeled samples. Recently, few-shot segmentation aiming at semantic segmentation on low sample data has…
Task-Adaptive Feature Transformer for Few-Shot Segmentation
Jun Seo, Young-Hyun Park, Sung-Whan Yoon +1
Few-shot learning allows machines to classify novel classes using only a few labeled samples. Recently, few-shot segmentation aiming at semantic segmentation on low sample data has…
Task-Adaptive Clustering for Semi-Supervised Few-Shot Classification
Jun Seo, Sung Whan Yoon, Jaekyun Moon
Few-shot learning aims to handle previously unseen tasks using only a small amount of new training data. In preparing (or meta-training) a few-shot learner, however, massive labele…
XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning
Sung Whan Yoon, Do-Yeon Kim, Jun Seo +1
Learning novel concepts while preserving prior knowledge is a long-standing challenge in machine learning. The challenge gets greater when a novel task is given with only a few lab…
TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning
Sung Whan Yoon, Jun Seo, Jaekyun Moon
Handling previously unseen tasks after given only a few training examples continues to be a tough challenge in machine learning. We propose TapNets, neural networks augmented with…
Meta-Learner with Linear Nulling
Sung Whan Yoon, Jun Seo, Jaekyun Moon
We propose a meta-learning algorithm utilizing a linear transformer that carries out null-space projection of neural network outputs. The main idea is to construct an alternative c…
On Reusing Pilots Among Interfering Cells in Massive MIMO
Jy-yong Sohn, Sung Whan Yoon, Jaekyun Moon
Pilot contamination, caused by the reuse of pilots among interfering cells, remains as a significant obstacle that limits the performance of massive multi-input multi-output antenn…
Capacity of Clustered Distributed Storage
Jy-yong Sohn, Beongjun Choi, Sung Whan Yoon +1
A new system model reflecting the clustered structure of distributed storage is suggested to investigate interplay between storage overhead and repair bandwidth as storage node fai…
Pilot Reuse Strategy Maximizing the Weighted-Sum-Rate in Massive MIMO Systems
Jy-yong Sohn, Sung Whan Yoon, Jaekyun Moon
Pilot reuse in multi-cell massive multi-input multi-output (MIMO) system is investigated where user groups with different priorities exist. Recent investigation on pilot reuse has…
Secure Clustered Distributed Storage Against Eavesdroppers
Beongjun Choi, Jy-yong Sohn, Sung Whan Yoon +1
This paper considers the security issue of practical distributed storage systems (DSSs) which consist of multiple clusters of storage nodes. Noticing that actual storage nodes cons…
Capacity of Clustered Distributed Storage
Jy-yong Sohn, Beongjun Choi, Sung Whan Yoon +1
A new system model reflecting the clustered structure of distributed storage is suggested to investigate bandwidth requirements for repairing failed storage nodes. Large data cente…
When Pilots Should Not Be Reused Across Interfering Cells in Massive MIMO
Ji Yong Sohn, Sung Whan Yoon, Jaekyun Moon
The pilot reuse issue in massive multi-input multi-output (MIMO) antenna systems with interfering cells is closely examined. This paper considers scenarios where the ratio of the c…