Publications

Filter by Year

Filter by Publication Type

Filter by Research Area

2024
[W46]
VACoDe: Visual Augmented Contrastive Decoding
Boryeong Cho*,
Sihyeon Kim*,
Sangmin Bae,
Sumyeong Ahn^,
Se-Young Yun^
ICML Workshop: "Trustworthy Multi-modal Foundation Models and AI Agents (TiFA)" 2024
[W45]
A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
Junghyun Lee,
Se-Young Yun,
Kwang-Sung Jun
ICML Workshop: "Aligning Reinforcement Learning Experimentalists and Theorists" 2024 (Oral)
[W44]
Gradient Descent with Polyak’s Momentum Finds Flatter Minima via Large Catapults
Prin Phunyaphibarn*,
Junghyun Lee*,
Bohan Wang,
Huishuai Zhang,
Chulhee Yun
ICML Workshop: "High-dimensional Learning Dynamics (HiLD): The Emergence of Structure and Reasoning" 2024
[paper]
[C79]
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL
Yunseon Choi,
Sangmin Bae,
Seonghyun Ban,
Minchan Jeong,
Chuheng Zhang,
Lei Song,
Li Zhao,
Jiang Bian,
Kee-Eung Kim
ACL 2024
[C78]
DistiLLM: Towards Streamlined Distillation for Large Language Models
Jongwoo Ko,
Sungnyun Kim,
Tianyi Chen,
Se-Young Yun
ICML 2024
[paper] [code]
[C77]
Synergistic Integration of Coordinate Network and Tensorial Feature for Improving Neural Radiance Fields from Sparse Inputs
Mingyu Kim,
Jun-Seong Kim,
Se-Young Yun,
Jin-Hwa Kim
ICML 2024
[paper] [video] [code]
[C76]
Fine-tuning Pre-trained Models for Robustness Under Noisy Labels
Sumyeong Ahn,
Sihyeon Kim,
Jongwoo Ko,
Se-Young Yun
IJCAI 2024
[paper]
[C75]
RepAugment: Input-Agnostic Representation-Level Augmentation for Respiratory Sound Classification
June-Woo Kim,
Miika Toikkanen,
Sangmin Bae,
Minseok Kim,
Ho-Young Jung
EMBC 2024
[J21]
The Multimodality Cell Segmentation Challenge: Toward Universal Solutions
Jun Ma*,
Ronald Xie*,
Shamini Ayyadhury*,
Cheng Ge*,
Anubha Gupta*,
Ritu Gupta*,
Song Gu*,
Yao Zhang*,
Gihun Lee,
Joonkee Kim,
Wei Lou,
Haofeng Li,
Eric Upschulte,
Timo Dickscheid,
Jose Guilherme ´ de Almeida,
Yixin Wang,
Lin Han,
Xin Yang,
Marco Labagnara,
Sahand Jamal Rahi,
Carly Kempster,
Alice Pollitt,
Leon Espinosa,
Tam Mignot,
Jan Moritz Middeke,
Jan-Niklas Eckardt,
Wangkai Li,
Zhaoyang Li,
ˆ Xiaochen Cai,
Bizhe Bai,
Noah F. Greenwald,
David Van Valen,
Erin Weisbart,
Beth A. Cimini,
Zhuoshi Li,
Chao Zuo,
Oscar Bruck,
Gary D. Bader,
Bo Wang
Nature Methods (2024)
[paper] [code]
[W43]
Towards Unbiased Evaluation of Detecting Unanswerable Questions in EHRSQL
Yongjin Yang,
Sihyeon Kim,
SangMook Kim,
Gyubok Lee,
Se-Young Yun,
Edward Choi
ICLR DPFM Workshop 2024
[paper]
[W42]
MA2E: Implicit Communication Through Masked Auto-Encoder in Multi-Agent Reinforcement Learning
Sehyeok Kang,
Yongsik Lee,
Gahee Kim,
Song Chong,
Se-Young Yun
ICLR GenAI4DM Workshop 2024
[C74]
Carpe diem: On the Evaluation of World Knowledge in Lifelong Language Models
Yujin Kim,
Jaehong Yoon,
Seonghyeon Ye,
Sangmin Bae,
Namgyu Ho,
Sung Ju Hwang,
Se-Young Yun
NAACL 2024
[J20]
Optimal Clustering from Noisy Binary Feedback
Kaito Ariu,
Jungseul Ok,
Alexandre Proutière,
Se-Young Yun
Machine Learning (2024)
[paper]
[C73]
FedSOL: Stabilized Orthogonal Learning in Federated Learning
Gihun Lee,
Minchan Jeong,
Sangmook Kim,
Jaehoon Oh,
Se-Young Yun
CVPR 2024
[paper]
[C72]
Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion
Junghyun Lee,
Se-Young Yun,
Kwang-Sung Jun
AISTATS 2024
[paper] [code]
[C71]
Re3val: Reinforced and Reranked Generative Retrieval
EuiYul Song,
Sangryul Kim,
Haeju Lee,
Joonkee Kim,
James Thorne
Findings of EACL 2024
[paper]
[C70]
Querying Easily Flip-flopped Samples for Deep Active Learning
Seong Jin Cho,
Gwangsu Kim,
Junghyun Lee,
Jinwoo Shin,
Chang D. Yoo
ICLR 2024
[paper]
[C69]
Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions
Taehyeon Kim*,
Joonkee Kim*,
Gihun Lee*,
Se-Young Yun
ICLR 2024 (Spotlight)
[paper] [code]
[C68]
Stethoscope-guided Supervised Contrastive Learning for Cross-domain Adaptation on Respiratory Sound Classification
June-Woo Kim,
Sangmin Bae,
Won-Yang Cho,
Byungjo Lee,
Ho-Young Jung
ICASSP 2024
[paper]
[C67]
STaR: Distilling Speech Temporal Relation for Lightweight Speech Self-Supervised Learning Models
Kangwook Jang,
Sungnyun Kim,
Hoirin Kim
ICASSP 2024 (Best Student Paper Award)
[paper]
[C66]
Leveraging Normalization Layer in Adapters With Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning
Yongjin Yang,
Taehyeon Kim,
Se-Young Yun
AAAI 2024
[paper]
2023
[W41]
Exploring the Retrieval Mechanism for Tabular Deep Learning
Felix den Breejen,
Sangmin Bae,
Stephen Cha,
Tae-Young Kim,
Seoung-Hyun Koh,
Se-Young Yun
NeurIPS Workshop: "Table Representation Learning" 2023
[paper]
[W40]
FedSoL: Bridging Global Alignment and Local Generality in Federated Learning
Gihun Lee,
Minchan Jeong,
SangMook Kim,
Jaehoon Oh,
Se-Young Yun
NeurIPS Workshop: "Federated Learning in the Age of Foundation Models" 2023
[paper]
[C65]
On the convergence time in graphical games: a locality-sensitive approach
Juho Hirvonen,
Laura Schmid,
Krishnendu Chatterjee,
Stefan Schmid
OPODIS 2023
[paper]
[C64]
Flooding with Absorption: An Efficient Protocol for Heterogeneous Bandits over Complex Networks
Junghyun Lee,
Laura Schmid,
Se-Young Yun
OPODIS 2023 (Best Student Paper Award)
[paper] [code]
[W39]
Recycle-and-Distill: Universal Compression Strategy for Transformer-based Speech SSL Models with Attention Map Reusing and Masking Distillation
Kangwook Jang*,
Sungnyun Kim*,
Se-Young Yun,
Hoirin Kim
NeurIPS Workshop: "Self-Supervised Learning - Theory and Practice" 2023
[paper] [code]
[W38]
Refined Tensorial Radiance Field: Harnessing Coordinate-Based Networks for Novel View Synthesis from Sparse Inputs
Mingyu Kim,
Jun-Seong Kim,
Se-Young Yun,
Jin-Hwa Kim
NeurIPS Workshop: "Deep Learning and Inverse Problems" 2023
[paper]
[W37]
Large Catapults in Momentum Gradient Descent with Warmup: An Empirical Study
Prin Phunyaphibarn*,
Junghyun Lee*,
Bohan Wang,
Huishuai Zhang,
Chulhee Yun
NeurIPS Workshop: "Mathematics of Modern Machine Learning (M3L)" 2023 (Oral)
[paper]
[W36]
Non-backtracking Graph Neural Networks
Seonghyun Park*,
Narae Ryu*,
Gahee Kim,
Dongyeop Woo,
Se-Young Yun,
Sungsoo Ahn
NeurIPS Workshop: "New Frontiers in Graph Learning" 2023 (Oral)
[paper]
[W35]
Node Mutual Information: Enhancing Graph Neural Networks for Heterophily
Seongjin Choi*,
Gahee Kim*,
Se-Young Yun
NeurIPS Workshop: "New Frontiers in Graph Learning" 2023
[paper]
[W34]
FedFN: Feature Normalization for Alleviating Data Heterogeneity Problem in Federated Learning
Seongyoon Kim,
Gihun Lee,
Jaehoon Oh^,
Se-Young Yun^
NeurIPS Workshop: "Federated Learning in the Age of Foundation Models" 2023
[paper]
[W33]
Distort, Distract, Decode: Instruction-Tuned Model Can Refine its Response from Noisy Instructions
Taehyeon Kim*,
Joonkee Kim*,
Gihun Lee*,
Se-Young Yun
NeurIPS Workshop: "Instruction Tuning and Instruction Following" 2023
[paper] [code]
[W32]
Parameter-Averaging Laws for Multitask Language Models
Woojin Chung,
Hyowon Cho,
James Thorne,
Se-Young Yun
NeurIPS Workshop: "Federated Learning in the Age of Foundation Models" 2023
[paper]
[W31]
Carpe Diem: On the Evaluation of World Knowledge in Lifelong Language Models
Yujin Kim,
Jaehong Yoon,
Seonghyeon Ye,
Sung Ju Hwang,
Se-Young Yun
NeurIPS Workshop: "SyntheticData4ML" 2023 (Oral)
[paper]
[C63]
Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning
Haeju Lee*,
Minchan Jeong*,
Se-Young Yun,
Kee-Eung Kim
Findings of EMNLP 2023
[paper]
[C62]
NASH: A Simple Unified Framework of Structured Pruning for Accelerating Encoder-Decoder Language Models
Jongwoo Ko*,
Seungjoon Park*,
Yujin Kim,
Sumyeong Ahn,
Du-Seong Chang,
Euijai Ahn,
Se-Young Yun
Findings of EMNLP 2023
[paper] [code]
[C61]
Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding
Sangmin Bae*,
Jongwoo Ko*,
Hwanjun Song,
Se-Young Yun
EMNLP 2023
[paper] [code]
[C60]
HARE: Explainable Hate Speech Detection with Step-by-Step Reasoning
Yongjin Yang*,
Joonkee Kim*,
Yujin Kim*,
Namgyu Ho,
James Thorne,
Se-Young Yun
Findings of EMNLP 2023
[paper] [code]
[C59]
PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning
Hojoon Lee*,
Hanseul Cho*,
Hyunseung Kim*,
Daehoon Gwak,
Joonkee Kim,
Jaegul Choo,
Se-Young Yun,
Chulhee Yun
NeurIPS 2023
[paper]
[C58]
Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint
Junghyun Lee*,
Hanseul Cho*,
Se-Young Yun,
Chulhee Yun
NeurIPS 2023
[paper] [code]
[C57]
Navigating Data Heterogeneity in Federated Learning: A Semi-Supervised Federated Object Detection
Taehyeon Kim,
Eric Lin,
Junu Lee,
Christian Lau,
Vaikkunth Mugunthan
NeurIPS 2023
[paper] [code]
[C56]
Meta-Learning with Adaptive Weighted Loss for Imbalanced Cold-Start Recommendation
Minchang Kim*,
Yongjin Yang*,
Jung Hyun Ryu,
Taesup Kim
CIKM 2023
[paper]
[W30]
Hierarchical Decomposition Framework for Feasibility-hard Combinatorial Optimization
Hanbum Ko*,
Minu Kim*,
Han-Seul Jeong,
Sunghoon Hong,
Deunsol Yoon,
Youngjoon Park,
Woohyung Lim,
Honglak Lee,
Moontae Lee,
Kanghoon Lee,
Sungbin Lim,
Sungryull Sohn
ICML Workshop: "Sampling and Optimization in Discrete Space" 2023
[paper]
[W29]
An Optimal Clustering Algorithm for the Labeled Stochastic Block Model
Kaito Ariu,
Se-Young Yun,
Alexandre Proutière
ICML Workshop: "Sampling and Optimization in Discrete Space" 2023
[paper]
[C55]
Recycle-and-Distill: Universal Compression Strategy for Transformer-based Speech SSL Models with Attention Map Reusing and Masking Distillation
Kangwook Jang*,
Sungnyun Kim*,
Se-Young Yun,
Hoirin Kim
INTERSPEECH 2023
[paper] [code]
[C54]
Patch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification
Sangmin Bae*,
June-Woo Kim*,
Wonyang Cho,
Hyerim Baek,
Soyoun Son,
Byungjo Lee,
Changwan Ha,
Kyungpil Tae,
Sungnyun Kim,
Se-Young Yun
INTERSPEECH 2023
[paper] [code]
[C53]
Large Language Models Are Reasoning Teachers
Namgyu Ho,
Laura Schmid,
Se-Young Yun
ACL 2023
[paper] [code]
[J19]
The StarCraft Multi-Agent Exploration Challenges: Learning Multi-Stage Tasks and Environmental Factors without Precise Reward Functions
Mingyu Kim*,
Jihwan Oh*,
Yongsik Lee,
Joonkee Kim,
SeongHwan Kim,
Song Chong,
Se-Young Yun
IEEE Access (2023)
[paper] [code]
[J18]
Quantitative Assessment can Stabilize Indirect Reciprocity under Imperfect Information
Laura Schmid,
Farbod Ekbatani,
Christian Hilbe,
Krishnendu Chatterjee
Nature Communications (2023)
[paper]
[W28]
Efficient Utilization of Pre-trained Model for Learning with Noisy Labels
Jongwoo Ko*,
Sumyeong Ahn*,
Se-Young Yun
ICLR Workshop: "Pitfalls of Limited Data and Computation for Trustworthy ML" 2023 (Oral)
[paper]
[C52]
Re-thinking Federated Active Learning based on Inter-class Diversity
SangMook Kim*,
Sangmin Bae*,
Hwanjun Song,
Se-Young Yun
CVPR 2023
[paper] [code]
[C51]
Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning
Sungnyun Kim*,
Sangmin Bae*,
Se-Young Yun
CVPR 2023
[paper] [video] [code]
[W27]
Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning
Sungnyun Kim*,
Sangmin Bae*,
Se-Young Yun
CVPR Workshop: "Fine-Grained Visual Categorization" 2023 (Invited)
[paper] [code]
[C50]
Revisiting Intermediate Layer Distillation for Compressing Language Models: An Overfitting Perspective
Jongwoo Ko,
Seungjoon Park,
Minchan Jeong,
Suk-Jin Hong,
Euijai Ahn,
Du-Seong Chang,
Se-Young Yun
Findings of EACL 2023
[paper] [code]
[C49]
CUDA: Curriculum of Data Augmentation for Long-tailed Recognition
Sumyeong Ahn*,
Jongwoo Ko*,
Se-Young Yun
ICLR 2023 (Spotlight, notable-top-25%)
[paper]
[C48]
Mitigating Dataset Bias by Using Per-Sample Gradient
Sumyeong Ahn*,
Seongyoon Kim*,
Se-Young Yun
ICLR 2023
[paper]
[C47]
Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles
Jung-hun Kim,
Se-Young Yun,
Minchan Jeong,
Junhyun Nam,
Jinwoo Shin,
Richard Combes
AISTATS 2023
[paper]
[C46]
Nearly Optimal Latent State Decoding in Block MDPs
Yassir Jedra*,
Junghyun Lee*,
Alexandre Proutière,
Se-Young Yun
AISTATS 2023
[paper] [code]
[C45]
Toward Risk-based Optimistic Exploration for Cooperative Multi-Agent Reinforcement Learning
Jihwan Oh*,
Joonkee Kim*,
Minchan Jeong,
Se-Young Yun
AAMAS 2023
[paper]
[C38]
A Gift from Label Smoothing: Robust Training with Adaptive Label Smoothing via Auxiliary Classifier under Label Noise
Jongwoo Ko*,
Bongsoo Yi*,
Se-Young Yun
AAAI 2023
[paper] [code]
[C37]
Self-Contrastive Learning: Single-viewed Supervised Contrastive Framework using Sub-network
Sangmin Bae*,
Sungnyun Kim*,
Jongwoo Ko,
Gihun Lee,
Seungjong Noh,
Se-Young Yun
AAAI 2023 (Oral)
[paper] [video] [code]
[C36]
Denoising After Entropy-based Debiasing A Robust Training Method for Dataset Bias with Noisy Labels
Sumyeong Ahn,
Se-Young Yun
AAAI 2023 (Oral)
[paper]
2022
[J17]
Meta-learning Amidst Heterogeneity and Ambiguity
KyeongRyeol Go,
Mingyu Kim,
Se-Young Yun
IEEE Access (2022)
[paper]
[C44]
Synergy with Translation Artifacts for Training and Inference in Multilingual Tasks
Jaehoon Oh*,
Jongwoo Ko*,
Se-Young Yun
EMNLP 2022
[paper] [code]
[C43]
Robust Streaming PCA
Daniel Bienstock*,
Minchan Jeong*,
Apurv Shukla*,
Se-Young Yun*
NeurIPS 2022
[paper]
[C42]
Preservation of the Global Knowledge by Not-True Distillation in Federated Learning
Gihun Lee* ,
Minchan Jeong*,
Yongjin Shin,
Sangmin Bae,
Se-Young Yun
NeurIPS 2022
[paper] [code]
[C41]
Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty
Jaehoon Oh*,
Sungnyun Kim*,
Namgyu Ho*,
Jin-Hwa Kim,
Hwanjun Song,
Se-Young Yun
NeurIPS 2022
[paper] [code]
[W26]
Revisiting the Activation Function for Federated Image Classification
Jaewoo Shin,
Taehyeon Kim,
Se-Young Yun
NeurIPS Workshop: "Federated Learning: Recent Advances and New Challenges" 2022
[paper] [code]
[W25]
Layover Intermediate Layer for Multi-Label Classification in Efficient Transfer Learning
Seongha Eom,
Taehyeon Kim,
Se-Young Yun
NeurIPS Workshop: "Has it Trained Yet? A Workshop for Algorithmic Efficiency in Practical Neural Network Training" 2022
[paper] [code]
[W24]
CUDA: Curriculum of Data Augmentation for Long-tailed Recognition
Sumyeong Ahn*,
Jongwoo Ko*,
Se-Young Yun
NeurIPS Workshop: "Machine Learning Safety" 2022
[paper]
[W23]
CUDA: Curriculum of Data Augmentation for Long-tailed Recognition
Sumyeong Ahn*,
Jongwoo Ko*,
Se-Young Yun
NeurIPS Workshop: "Distribution Shifts: Connecting Methods and Applications" 2022
[paper]
[W22]
Mitigating Dataset Bias by Using Per-Sample Gradient
Sumyeong Ahn*,
Seongyoon Kim*,
Se-Young Yun
NeurIPS Workshop: "Machine Learning Safety" 2022
[paper]
[W21]
Mitigating Dataset Bias by Using Per-Sample Gradient
Sumyeong Ahn*,
Seongyoon Kim*,
Se-Young Yun
NeurIPS Workshop: "Distribution Shifts: Connecting Methods and Applications" 2022
[paper]
[W20]
Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning
Sungnyun Kim*,
Sangmin Bae*,
Se-Young Yun
NeurIPS Workshop: "Self-Supervised Learning - Theory and Practice" 2022
[paper]
[J16]
Estimation of Cardiac Short Axis Slice Levels with a Cascaded Deep Convolutional and Recurrent Neural Network Model
Namgyu Ho,
Yoon-Chul Kim
Tomography (2022)
[paper]
[C40]
ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning
Jaehoon Oh*,
Sungnyun Kim*,
Namgyu Ho*,
Jin-Hwa Kim,
Hwanjun Song,
Se-Young Yun
CIKM 2022 (Short)
[paper] [video]
[C39]
FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning
Sangmook Kim,
Wonyoung Shin,
Soohyuk Jang,
Hwanjun Song,
Se-Young Yun
CIKM 2022 (Long)
[paper]
[J15]
Interpretable Deep Learning Model for Analyzing the Relationship between the Electronic Structure and Chemisorption Property
Doosun Hong*,
Jaehoon Oh*,
Kihoon Bang,
Soonho Kwon,
Se-Young Yun,
Hyuck Mo Lee
The Journal of Physical Chemistry Letters
[paper]
[J14]
Accelerated MM Algorithms for Ranking Scores Inference from Comparison Data
Milan Vojnovic,
Se-Young Yun,
Kaifang Zhou
Operations Research (2022)
[paper]
[J13]
Test Score Algorithms for Budgeted Stochastic Utility Maximization
Dabeen Lee,
Milan Vojnovic,
Se-Young Yun
INFORMS Journal of Optimization (2022)
[paper]
[W19]
ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning
Jaehoon Oh*,
Sungnyun Kim*,
Namgyu Ho*,
Jin-Hwa Kim,
Hwanjun Song,
Se-Young Yun
ICML Workshop: "Updatable Machine Learning" 2022
[paper]
[W18]
The StarCraft Multi-Agent Challenges+ : Learning of Multi-Stage Tasks and Environmental Factors without Precise Reward Functions
Mingyu Kim*,
Jihwan Oh*,
Yongsik Lee,
Joonkee Kim,
SeongHwan Kim,
Song Chong,
Se-Young Yun
ICML Workshop : "AI for Agent Based Modeling" 2022 (Spotlight)
[paper] [code]
[W17]
LG-FAL : Federated Active Learning Strategy using Local and Global Models
SangMook Kim*,
Sangmin Bae*,
Hwanjun Song,
Se-Young Yun
ICML Workshop: "Adaptive Experimental Design and Active Learning in the Real World" 2022
[paper]
[W16]
Supernet Training for Federated Image Classification under System Heterogeneity
Taehyeon Kim,
Se-Young Yun
ICML Workshop: "Dynamic Neural Networks" 2022 (Oral)
[paper]
[W15]
Revisiting the Updates of a Pre-trained Model for Few-shot Learning
Yujin Kim*,
Jaehoon Oh*,
Sungnyun Kim,
Se-Young Yun
ICML Workshop: "Updatable Machine Learning" 2022 (Oral)
[paper]
[W14]
Revisiting Architecture-aware Knowledge Distillation: Smaller Models and Faster Search
Taehyeon Kim,
Heesoo Myeong,
Se-Young Yun
ICML Workshop: "Hardware Aware Efficient Training (HAET)” 2022
[paper]
[W13]
Real-time and Explainable Detection of Epidemics with Global News Data
Sungnyun Kim*,
Jaewoo Shin*,
Seongha Eom,
Jihwan Oh,
Se-Young Yun
ICML Workshop: "Healthcare AI and COVID-19" 2022
[paper] [video] [code]
[W12]
Risk Perspective Exploration in Distributional Reinforcement Learning
Jihwan Oh,
Joonkee Kim,
Se-Young Yun
ICML Workshop: "AI for Agent Based Modeling" 2022
[paper]
[C35]
Rotting infinitely many-armed bandits
Jung-hun Kim,
Milan Vojnovic,
Se-Young Yun
ICML 2022
[paper]
[J12]
Revisiting Orthogonality Regularization: A Study for Convolutional Neural Networks in Image Classification
Taehyeon Kim,
Se-Young Yun
IEEE Access (2022)
[paper]
[J11]
Calibration of Few-Shot Classification Tasks: Mitigating Misconfidence From Distribution Mismatch
Sungnyun Kim,
Se-Young Yun
IEEE Access (2022)
[paper] [code]
[W11]
ALASCA: Rethinking Label Smoothing for Deep Learning Under Label Noise
Jongwoo Ko,
Bongsoo Yi,
Se-Young Yun
ICML Workshop: “Principle of Distribution Shift (PODS)” 2022
[paper]
[C34]
FedBABU: Towards Enhanced Representation for Federated Image Classification
Jaehoon Oh*,
SangMook Kim*,
Se-Young Yun
ICLR 2022
[paper] [code]
[C33]
Neural Processes with Stochastic Attention: Paying more attention to the context dataset
Mingyu Kim,
Kyeongryeol Go,
Se-Young Yun
ICLR 2022
[paper] [video] [code]
[J10]
Deep Learning-Based Cataract Detection and Grading from Slit-Lamp and Retro-Illumination Photographs: Model Development and Validation Study
Ki Young Son*,
Jongwoo Ko*,
Eunseok Kim,
Si Young Lee,
Min-Ji Kim,
Jisang Han,
Eunhae Shin,
Tae-Young Chung,
Dong Hui Lim
Ophthalmology Science (2022)
[paper]
[C32]
Fast and Efficient MMD-based Fair PCA via Optimization over Stiefel Manifold
Junghyun Lee,
Gwangsu Kim,
Matt Olfat,
Mark Hasegawa-Johnson,
Chang D. Yoo
AAAI 2022
[paper] [code]
2021
[C31]
FINE Samples for Learning with Noisy Labels
Taehyeon Kim*,
Jongwoo Ko*,
Sangwook Cho,
Jinhwan Choi,
Se-Young Yun
NeurIPS 2021
[paper] [code]
[W10]
FedBABU: Towards Enhanced Representation for Federated Image Classification
Jaehoon Oh,
SangMook Kim,
Se-Young Yun
NeurIPS Workshop: "New Frontiers in Federated Learning: Privacy, Fairness, Robustness, Personalization and Data Ownership" 2021
[paper]
[W9]
Neural Processes with Stochastic Attention: Paying more attention to the context dataset
Mingyu Kim,
Kyeongryeol Go,
Se-Young Yun
NeurIPS Workshop: "5th Workshop on Meta-Learning" 2021
[paper]
[C30]
Preliminary Evaluation of SWAY in Permutation Decision Space via a Novel Euclidean Embedding
Junghyun Lee*,
Chani Jung*,
Yoo Hwa Park*,
Dongmin Lee*,
Juyeon Yoon,
Shin Yoo
SSBSE 2021
[paper] [code]
[C29]
Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation
Taehyeon Kim*,
Jaehoon Oh*,
Nakyil Kim,
Sangwook Cho,
Se-Young Yun
IJCAI 2021
[paper] [code]
[C28]
Improved Regret Bounds of Bilinear Bandits using Action Space Analysis
Kyoungseok Jang,
Kwang-Sung Jun,
Se-Young Yun,
Wanmo Kang
ICML 2021
[paper]
[J9]
Deep Gaussian process models for integrating multifidelity experiments with nonstationary relationships
Jongwoo Ko,
Heeyoung Kim
IISE Transactions (2022)
[paper]
[C27]
BOIL: Towards Representation Change for Few-shot Learning
Jaehoon Oh*,
Hyungjun Yoo*,
ChangHwan Kim,
Se-Young Yun
ICLR 2021
[paper] [code]
[W8]
TornadoAggregate: Accurate and Scalable Federated Learning via the Ring-based Architecture
Jin-woo Lee,
Jaehoon Oh,
Sungsu Lim,
Se-Young Yun,
Jae-Gil Lee
AAAI Workshop: "Toward Robust, Secure and Efficient Machine Learning" 2021
[paper]
2020
[J8]
Clustering in Block Markov Chains
Jaron Sanders,
Alexandre Proutière,
Se-Young Yun
Annals of Statistics (2020)
[paper]
[W7]
Adaptive Local Bayesian Optimization Over Multiple Discrete Variables
Taehyeon Kim*,
Jaeyeon Ahn*,
Nakyil Kim*,
Se-Young Yun
NeurIPS Workshop: "Competition Track on Black-Box Optimization Challenge" 2020
[paper]
[C26]
Regret in Online Recommendation Systems
Kaito Ariu,
Narae Ryu,
Se-Young Yun,
Alexandre Proutière
NeurIPS 2020
[paper]
[W6]
MixCo: Mix-up Contrastive Learning for Visual Representation
Sungnyun Kim*,
Gihun Lee*,
Sangmin Bae*,
Se-Young Yun
NeurIPS Workshop: "Self-Supervised Learning - Theory and Practice" 2020
[paper] [code]
[W5]
FEWER: Federated Weight Recovery
Yongjin Shin,
Gihun Lee,
Seungjae Shin,
Se-Young Yun,
Il-Chul Moon
DistributedML: 1st Workshop on Distributed Machine Learning 2020
[paper]
[W4]
Precipitation Nowcasting Using Grid-based Data in South Korea Region
ChangHwan Kim,
Se-Young Yun
ICDM Workshop: The 4th International Workshop on Big Data Analysis for Smart Energy (BigData4SmartEnergy) 2020
[paper]
[W3]
SIPA: A Simple Framework for Efficient Networks
Gihun Lee*,
Sangmin Bae*,
Jaehoon Oh,
Se-Young Yun
ICDM Workshop: The 4th International Workshop on Big Data Analysis for Smart Energy (BigData4SmartEnergy) 2020
[paper]
[C25]
Convergence Rates of Gradient Descent and MM Algorithms for Bradley-Terry Models
Milan Vojnovic,
Se-Young Yun,
Kaifang Zhou
AISTATS 2020
[paper]
[J7]
A Test Score-Based Approach to Stochastic Submodular Optimization
Shreyas Sekar,
Milan Vojnovic,
Se-Young Yun
Management Science (2021)
[paper]
[J6]
Reinforcement with Fading Memories
Kuang Xu,
Se-Young Yun
Mathematics of Operations Research (2020)
[paper]
[C24]
Accelerating Randomly Projected Gradient with Variance Reduction
SeongYoon Kim,
Se-Young Yun
BigComp 2020
[paper]
2019
[C23]
Optimal Sampling and Clustering in the Stochastic Block Model
Se-Young Yun,
Alexandre Proutière
NeurIPS 2019
[paper]
[C22]
Spectral Approximate Inference
Sejun Park,
Eunho Yang,
Se-Young Yun,
Jinwoo Shin
ICML 2019
[paper]
2018
[W2]
Ted Talk Recommender Using Speech Transcripts
Jaehoon Oh*,
Injung Lee*,
Yeon Seonwoo*,
Simin Sung,
Ilbong Kwon,
Jae-Gil Lee
ASONAM Demos and Exhibitions 2018
[paper]
[C21]
Reinforcement with Fading Memories
Kuang Xu,
Se-Young Yun
SIGMETRICS (Extended Abstracts) 2018
[paper]
[C20]
Noisy Power Method with Grassmann Average
Se-Young Yun
BigComp 2018
[paper]
2017
[W1]
Non-Stationary Streaming PCA
Daniel Bienstock,
Apurv Shukla,
Se-Young Yun
NeurIPS Workshop: "Time Series Workshop" 2017
[paper]
[J5]
Game Theoretic Perspective of Optimal CSMA
Hyeryung Jang,
Se-Young Yun,
Jinwoo Shin,
Yung Yi
IEEE Transactions on Wireless Communications (2018)
[paper]
[C19]
Collaborative Clustering: Sample Complexity and Efficient Algorithms
Jungseul Ok,
Se-Young Yun,
Alexandre Proutière,
Rami Mochaourab
ALT 2017
[paper]
2016
[C18]
Optimal Cluster Recovery in the Labeled Stochastic Block Model
Se-Young Yun,
Alexandre Proutière
NIPS 2016
[paper]
[C17]
Distributed coordination maximization over networks: a stochastic approximation approach
Hyeryung Jang,
Se-Young Yun,
Jinwoo Shin,
Yung Yi
MobiHoc 2016
[paper]
[C16]
Parameter Estimation for Generalized Thurstone Choice Models
Milan Vojnovic,
Se-Young Yun
ICML 2016
[paper]
[J4]
Distributed Medium Access Over Time-Varying Channels
Se-Young Yun,
Jinwoo Shin,
Yung Yi
IEEE/ACM Transactions on Networking (2016)
[paper]
2015
[C15]
Fast and Memory Optimal Low-Rank Matrix Approximation
Se-Young Yun,
Marc Lelarge,
Alexandre Proutière
NeurIPS 2015
[paper]
[J3]
Delay Optimal CSMA With Linear Virtual Channels Under a General Topology
Donggyu Yun,
Dongmyung Lee,
Se-Young Yun,
Jinwoo Shin,
Yung Yi
IEEE/ACM Transactions on Networking (2016)
[paper]
[J2]
CSMA Using the Bethe Approximation: Scheduling and Utility Maximization
Se-Young Yun,
Jinwoo Shin,
Yung Yi
IEEE Transactions on Information Theory (2015)
[paper]
[C14]
Distributed Proportional Fair Load Balancing in Heterogeneous Systems
Se-Young Yun,
Alexandre Proutière
SIGMETRICS 2015
[paper]
2014
[C13]
Streaming, Memory Limited Algorithms for Community Detection
Se-Young Yun,
Marc Lelarge,
Alexandre Proutière
NIPS 2014
[paper]
[C12]
Community Detection via Random and Adaptive Sampling
Se-Young Yun,
Alexandre Proutière
COLT 2014
[paper]
[C11]
Provable per-link delay-optimal CSMA for general wireless network topology
Dongmyung Lee,
Donggyu Yun,
Jinwoo Shin,
Yung Yi,
Se-Young Yun
IEEE INFOCOM 2014
[paper]
[C10]
Distributed learning for utility maximization over CSMA-based wireless multihop networks
Hyeryung Jang,
Se-Young Yun,
Jinwoo Shin,
Yung Yi
IEEE INFOCOM 2014
[paper]
2013
[C9]
CSMA over time-varying channels: optimality, uniqueness and limited backoff rate
Se-Young Yun,
Jinwoo Shin,
Yung Yi
MobiHoc 2013 (Best Paper Award)
[paper]
[C8]
CSMA using the Bethe approximation for utility maximization
Se-Young Yun,
Jinwoo Shin,
Yung Yi
IEEE ISIT 2013
[paper]
2012
[C7]
Optimal CSMA: A survey
Se-Young Yun,
Yi Yung,
Jinwoo Shin,
Do Young Eun
IEEE ICCS 2012
[paper]
[C6]
From Glauber dynamics to Metropolis algorithm: Smaller delay in optimal CSMA
Chul-Ho Lee,
Do Young Eun,
Se-Young Yun,
Yung Yi
IEEE ISIT 2012
[paper]
[J1]
The Economic Effects of Sharing Femtocells
Se-Young Yun,
Yung Yi,
Dong-Ho Cho,
Jeonghoon Mo
IEEE Journal on Selected Areas in Communications (2012)
[paper]
2011
[C5]
Open or close: On the sharing of femtocells
Se-Young Yun,
Yung Yi,
Dong-Ho Cho,
Jeonghoon Mo
IEEE INFOCOM 2011
[paper]
[C4]
Multi-channel MAC protocol for QoS support in ad-hoc network
Kyung-Seop Shin,
Se-Young Yun,
Dong-Ho Cho
IEEE CCNC 2011
[paper]
2010
[C3]
Traffic density based power control scheme for femto AP
Se-Young Yun,
Dong-Ho Cho
IEEE PIMRC 2010
[paper]
[C2]
On the Pricing of Femtocell Services
Se-Young Yun,
Yung Yi,
Dongho Cho,
Jeonghoon Mo
ACM CFI 2010
[paper]
2009
[C1]
Decentralized power control scheme in femtocell networks: A game theoretic approach
Eun Jin Hong,
Se-Young Yun,
Dong-Ho Cho
IEEE PIMRC 2009
[paper]