Se-Young Yun

发表

Game Theoretic Perspective of Optimal CSMA

Jinwoo Shin, Yung Yi, Se-Young Yun, 2018, IEEE Transactions on Wireless Communications.

ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning

Jin-Hwa Kim, Se-Young Yun, Hwanjun Song, 2022, International Conference on Information and Knowledge Management.

FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning

Se-Young Yun, Sangmook Kim, Hwanjun Song, 2022, ArXiv.

Revisiting the Updates of a Pre-trained Model for Few-shot Learning

Se-Young Yun, Jaehoon Oh, Sungnyun Kim, 2022, ArXiv.

Benchmark Dataset for Precipitation Forecasting by Post-Processing the Numerical Weather Prediction

Se-Young Yun, Namgyu Ho, Taehyeon Kim, 2022, 2206.15241.

Risk Perspective Exploration in Distributional Reinforcement Learning

Se-Young Yun, Ji-Yun Oh, Joonkee Kim, 2022, ArXiv.

Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles

Jinwoo Shin, Richard Combes, Se-Young Yun, 2017, 1703.01347.

Revisiting Architecture-aware Knowledge Distillation: Smaller Models and Faster Search

Se-Young Yun, Heesoo Myeong, Taehyeon Kim, 2022, ArXiv.

Mitigating Dataset Bias by Using Per-sample Gradient

Se-Young Yun, Sumyeong Ahn, Seongyoon Kim, 2022, ArXiv.

ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning

Jin-Hwa Kim, Se-Young Yun, Hwanjun Song, 2022, International Conference on Information and Knowledge Management.

Rotting infinitely many-armed bandits

M. Vojnovic, Se-Young Yun, Jung-hun Kim, 2022, ICML.

Revisiting the Updates of a Pre-trained Model for Few-shot Learning

Se-Young Yun, Jaehoon Oh, Sungnyun Kim, 2022, ArXiv.

Benchmark Dataset for Precipitation Forecasting by Post-Processing the Numerical Weather Prediction

Se-Young Yun, Namgyu Ho, Taehyeon Kim, 2022, ArXiv.

Accelerated MM Algorithms for Inference of Ranking Scores from Comparison Data

Se-Young Yun, Kaifang Zhou, M. Vojnović, 2022, Oper. Res..

Calibration of Few-Shot Classification Tasks: Mitigating Misconfidence from Distribution Mismatch

Se-Young Yun, Sungnyun Kim, 2022, IEEE Access.

ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning

Jin-Hwa Kim, Se-Young Yun, Hwanjun Song, 2022, ArXiv.

Revisiting Orthogonality Regularization: A Study for Convolutional Neural Networks in Image Classification

Se-Young Yun, Taehyeon Kim, 2022, IEEE Access.

Robust Streaming PCA

D. Bienstock, Se-Young Yun, Minchan Jeong, 2019, NeurIPS.

Understanding Cross-Domain Few-Shot Learning: An Experimental Study

Jin-Hwa Kim, Se-Young Yun, Hwanjun Song, 2022, ArXiv.

Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty

Jin-Hwa Kim, Se-Young Yun, Hwanjun Song, 2022, NeurIPS.

Supernet Training for Federated Image Classification under System Heterogeneity

Se-Young Yun, Taehyeon Kim, 2022, arXiv.org.

Preservation of the Global Knowledge by Not-True Distillation in Federated Learning

Se-Young Yun, Minchan Jeong, Gihun Lee, 2021, 2106.03097.

Synergy with Translation Artifacts for Training and Inference in Multilingual Tasks

Se-Young Yun, Jaehoon Oh, Jongwoo Ko, 2022, EMNLP.

Demystifying the Base and Novel Performances for Few-shot Class-incremental Learning

Se-Young Yun, Jaehoon Oh, 2022, ArXiv.

Layover Intermediate Layer for Multi-Label Classification in Efficient Transfer Learning

Se-Young Yun, Taehyeon Kim, Seong-Hoon Eom, 2022 .

MEDIAR: Harmony of Data-Centric and Model-Centric for Multi-Modality Microscopy

Se-Young Yun, Sangmook Kim, Joonkee Kim, 2022, Cell Segmentation Challenge @ NeurIPS.

Self-Contrastive Learning: Single-Viewed Supervised Contrastive Framework Using Sub-network

Se-Young Yun, Sungnyun Kim, Gihun Lee, 2021, AAAI.

Denoising after Entropy-based Debiasing A Robust Training Method for Dataset Bias with Noisy Labels

Se-Young Yun, Sumyeong Ahn, 2022, AAAI.

Large Language Models Are Reasoning Teachers

Se-Young Yun, Namgyu Ho, Laura Schmid, 2022, ArXiv.

ALASCA: Rethinking Label Smoothing for Deep Learning Under Label Noise

Se-Young Yun, Jongwoo Ko, Bongsoo Yi, 2022, ArXiv.

Real-time and Explainable Detection of Epidemics with Global News Data

Se-Young Yun, Sungnyun Kim, Ji-Yun Oh, 2022 .

Neural Processes with Stochastic Attention: Paying more attention to the context dataset

Se-Young Yun, Mingyu Kim, Kyeongryeol Go, 2022, ICLR.

Toward Risk-based Optimistic Exploration for Cooperative Multi-Agent Reinforcement Learning

Se-Young Yun, Ji-Yun Oh, Joonkee Kim, 2023, AAMAS.

How to Fine-tune Models with Few Samples: Update, Data Augmentation, and Test-time Augmentation

Se-Young Yun, Jaehoon Oh, Sungnyun Kim, 2022, 2205.07874.

A Survey of Supernet Optimization and its Applications: Spatial and Temporal Optimization for Neural Architecture Search

Se-Young Yun, Hayeon Lee, Taehyeon Kim, 2022, 2204.03916.

Mitigating Dataset Bias by Using Per-sample Gradient

Se-Young Yun, Sumyeong Ahn, Seongyoon Kim, 2022, ICLR.

Preservation of the Global Knowledge by Not-True Self Knowledge Distillation in Federated Learning pdf

Se-Young Yun, Yongjin Shin, Gihun Lee, 2021, ArXiv.

FedBABU: Towards Enhanced Representation for Federated Image Classification

Se-Young Yun, Sangmook Kim, Jaehoon Oh, 2021, ICLR.

FINE Samples for Learning with Noisy Labels

Se-Young Yun, Taehyeon Kim, Jongwoo Ko, 2021, NeurIPS.

FedRN

Se-Young Yun, Sangmook Kim, Hwanjun Song, 2022, Proceedings of the 31st ACM International Conference on Information & Knowledge Management.

Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation pdf

Se-Young Yun, Taehyeon Kim, Jaehoon Oh, 2021, IJCAI.

TornadoAggregate: Accurate and Scalable Federated Learning via the Ring-Based Architecture

Se-Young Yun, Sungsu Lim, Jin-Woo Lee, 2020, ArXiv.

Accurate and Fast Federated Learning via Combinatorial Multi-Armed Bandits pdf

Taehyeon Kim, Sangmin Bae, Jin-woo Lee, 2020, ArXiv.

Optimal Clustering from Noisy Binary Feedback pdf

Jungseul Ok, Se-Young Yun, Kaito Ariu, 2019, ArXiv.

Large Language Models Are Reasoning Teachers

Se-Young Yun, Namgyu Ho, Laura Schmid, 2022, ACL.

Preservation of the Global Knowledge by Not-True Distillation in Federated Learning

Se-Young Yun, Minchan Jeong, Gihun Lee, 2021, NeurIPS.

Region-Conditioned Orthogonal 3D U-Net for Weather4Cast Competition

Se-Young Yun, Kijung Shin, Taehyeon Kim, 2022, ArXiv.

Medium Access over Time-varying Channels with Limited Sensing Cost pdf

Jinwoo Shin, Yung Yi, Se-Young Yun, 2012, ArXiv.

Revisiting Intermediate Layer Distillation for Compressing Language Models: An Overfitting Perspective

Se-Young Yun, Minchan Jeong, Jongwoo Ko, 2023, FINDINGS.

Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning

Se-Young Yun, Sungnyun Kim, Sangmin Bae, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Recycle-and-Distill: Universal Compression Strategy for Transformer-based Speech SSL Models with Attention Map Reusing and Masking Distillation

Se-Young Yun, Se-Young Yun, Sungnyun Kim, 2023, ArXiv.

The StarCraft Multi-Agent Challenges+ : Learning of Multi-Stage Tasks and Environmental Factors without Precise Reward Functions

Se-Young Yun, Mingyu Kim, Ji-Yun Oh, 2022, ArXiv.

FEWER: Federated Weight Recovery

Yongjin Shin, Gihun Lee, Seungjae Shin, 2020, DistributedML@CoNEXT.

Self-Contrastive Learning: An Efficient Supervised Contrastive Framework with Single-view and Sub-network

Se-Young Yun, Sungnyun Kim, Gihun Lee, 2022 .

Self-Contrastive Learning

Se-Young Yun, Sungnyun Kim, Gihun Lee, 2021, ArXiv.

Cross-Modal Retrieval Meets Inference: Improving Zero-Shot Classification with Cross-Modal Retrieval

Se-Young Yun, Jaehoon Oh, Namgyu Ho, 2023, ArXiv.

CUDA: Curriculum of Data Augmentation for Long-Tailed Recognition

Se-Young Yun, Sumyeong Ahn, Jongwoo Ko, 2023, ICLR.

Flooding with Absorption: An Efficient Protocol for Heterogeneous Bandits over Complex Networks

Se-Young Yun, Laura Schmid, Junghyun Lee, 2023, OPODIS.

Interpretable Deep Learning Model for Analyzing the Relationship between the Electronic Structure and Chemisorption Property.

Se-Young Yun, Kihoon Bang, Soonho Kwon, 2022, The journal of physical chemistry letters.

A Gift from Label Smoothing: Robust Training with Adaptive Label Smoothing via Auxiliary Classifier under Label Noise

Se-Young Yun, Jongwoo Ko, Bongsoo Yi, 2022, AAAI.

FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning

Se-Young Yun, Sangmook Kim, Hwanjun Song, 2022, International Conference on Information and Knowledge Management.

ALASCA: Rethinking Label Smoothing for Deep Learning Under Label Noise

Se-Young Yun, Jongwoo Ko, Bongsoo Yi, 2022, ArXiv.

Recycle-and-Distill: Universal Compression Strategy for Transformer-based Speech SSL Models with Attention Map Reusing and Masking Distillation

Se-Young Yun, Sungnyun Kim, Hoi-Rim Kim, 2023, INTERSPEECH 2023.

PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning

Chulhee Yun, J. Choo, Se-Young Yun, 2023, 2306.10711.

SuperNet in Neural Architecture Search: A Taxonomic Survey

Se-Young Yun, Hayeon Lee, Taehyeon Kim, 2022, ArXiv.

FedSOL: Stabilized Orthogonal Learning in Federated Learning

Se-Young Yun, Sangmook Kim, Jaehoon Oh, 2023, 2308.12532.

FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning

Se-Young Yun, Sangmook Kim, Jaehoon Oh, 2023, 2308.12532.

Re-Thinking Federated Active Learning Based on Inter-Class Diversity

Se-Young Yun, Sangmook Kim, Hwanjun Song, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles

Jinwoo Shin, Richard Combes, Se-Young Yun, 2017, AISTATS.