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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<link rel="icon" href="logo/log_logo.png" type="image/png">
<title>Publications | Lee Optimization Group</title>
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<header>
<h1>Lee Optimization Group</h1>
<nav>
<a href="index.html">Home</a>
<a href="research.html">Research</a>
<a href="publications.html">Publications</a>
<a href="group.html">Members</a>
<a href="hiring.html">Hiring</a>
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</header>
<h2>Publications</h2>
<!-- ===== 2026 ===== -->
<h3 class="year-divider">2026</h3>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/2602.18181v1" target="_blank">
SeedFlood: A Step Toward Scalable Decentralized Training of LLMs
</a>
</div>
<div class="paper-authors">Jihun Kim, Namhoon Lee</div>
<div class="paper-venue">arXiv 2026</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://www.arxiv.org/abs/2602.03515" target="_blank">
Mitigating Staleness in Asynchronous Pipeline Parallelism via Basis Rotation
</a>
</div>
<div class="paper-authors">Hyunji Jung*, Sungbin Shin*, Namhoon Lee</div>
<div class="paper-venue">arXiv 2026</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/2510.01650" target="_blank">
The Unseen Frontier: Pushing the Limits of LLM Sparsity with Surrogate-Free ADMM
</a>
</div>
<div class="paper-authors">Kwanhee Lee, Hyeondo Jang, Dongyeop Lee, Dan Alistarh, Namhoon Lee</div>
<div class="paper-venue">ICLR 2026</div>
</div>
<!-- ===== 2025 ===== -->
<h3 class="year-divider">2025</h3>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/2510.25798" target="_blank">
MemIEC: A Step Toward Continual and Compositional Knowledge Editing
</a>
</div>
<div class="paper-authors">Jin Seong*, Jiyun Park*, Wencke Liermann, Hongseok Choi, Yoonji Nam, Hyun Kim, Soojong Lim, Namhoon Lee</div>
<div class="paper-venue">NeurIPS 2025</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/2505.16705" target="_blank">
An Analysis of Concept Bottleneck Models: Measuring, Understanding, and Mitigating the Impact of Noisy Annotations
</a>
</div>
<div class="paper-authors">Seonghwan Park, Jueun Mun, Donghyun Oh, Namhoon Lee</div>
<div class="paper-venue">NeurIPS 2025</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/2311.17539" target="_blank">
Critical Influence of Overparameterization on Sharpness-aware Minimization
</a>
</div>
<div class="paper-authors">Sungbin Shin*, Dongyeop Lee*, Maksym Andriushchenko, Namhoon Lee</div>
<div class="paper-venue">UAI 2025; ICML 2023 Workshop on High-dimensional Learning Dynamics</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/2506.06866" target="_blank">
SAFE: Finding Sparse and Flat Minima to Improve Pruning
</a>
</div>
<div class="paper-authors">Dongyeop Lee, Kwanhee Lee, Jinseok Chung, Namhoon Lee</div>
<div class="paper-venue">ICML 2025 <span class="spotlight">(Spotlight)</span></div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/2502.18153" target="_blank">
SASSHA: Sharpness-aware Adaptive Second-order Optimization with Stable Hessian Approximation
</a>
</div>
<div class="paper-authors">Dahun Shin*, Dongyeop Lee*, Jinseok Chung, Namhoon Lee</div>
<div class="paper-venue">ICML 2025</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/2504.06838" target="_blank">
ZIP: An Efficient Zeroth-order Prompt Tuning for Black-box Vision-Language Models
</a>
</div>
<div class="paper-authors">Seonghwan Park, Jaehyeon Jeong, Yongjun Kim, Jaeho Lee, Namhoon Lee</div>
<div class="paper-venue">ICLR 2025</div>
</div>
<!-- ===== 2024 ===== -->
<h3 class="year-divider">2024</h3>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/2406.15524" target="_blank">
Rethinking Pruning Large Language Models: Benefits and Pitfalls of Reconstruction Error Minimization
</a>
</div>
<div class="paper-authors">Sungbin Shin, Wonpyo Park, Jaeho Lee, Namhoon Lee</div>
<div class="paper-venue">EMNLP 2024</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/2302.10494" target="_blank">
The Role of Masking for Efficient Supervised Knowledge Distillation of Vision Transformers
</a>
</div>
<div class="paper-authors">Seungwoo Son, Jegwang Ryu, Namhoon Lee, Jaeho Lee</div>
<div class="paper-venue">ECCV 2024; ICLR 2023 Workshop</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/2304.14082" target="_blank">
JaxPruner: A Concise Library for Sparsity Research
</a>
</div>
<div class="paper-authors">
Joo Hyung Lee, Wonpyo Park, Nicole Mitchell, Jonathan Pilault, Johan Obando-Ceron,
Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh,
Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao,
Xingyao Zhang, Trevor Gale, Aart Bik, Woohyun Han, Milen Ferez,
Zhonglin Han, Hong-Seok Kim, Yann Dauphin,
Gintare Karolina Dziugaite, Pablo Samuel Castro, Utku Evci
</div>
<div class="paper-venue">CPAL 2024 <span class="spotlight">(Oral)</span>; ICLR 2023 Workshop on Sparsity in Neural Networks</div>
</div>
<!-- ===== 2023 ===== -->
<h3 class="year-divider">2023</h3>
<div class="paper">
<div class="paper-title">
<a href="https://opt-ml.org/papers.html" target="_blank">
Pruning Neural Networks with Velocity-Constrained Optimization
</a>
</div>
<div class="paper-authors">Donghyun Oh*, Jinseok Chung*, Namhoon Lee</div>
<div class="paper-venue">NeurIPS 2023 Workshop on Optimization for Machine Learning</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/2302.14260" target="_blank">
A Closer Look at the Intervention Procedure of Concept Bottleneck Models
</a>
</div>
<div class="paper-authors">Sungbin Shin, Yohan Jo, Sungsoo Ahn, Namhoon Lee</div>
<div class="paper-venue">ICML 2023; NeurIPS 2022 Workshop on Trustworthy and Socially Responsible ML</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://sites.google.com/view/hidimlearning/papers" target="_blank">
On the Effectiveness of Sharpness-Aware Minimization with Large Mini-batches
</a>
</div>
<div class="paper-authors">Jinseok Chung, Seonghwan Park, Jaeho Lee, Namhoon Lee</div>
<div class="paper-venue">ICML 2023 Workshop on High-dimensional Learning Dynamics</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://fl-icml2023.github.io/" target="_blank">
FedFwd: Federated Learning without Backpropagation
</a>
</div>
<div class="paper-authors">Seonghwan Park, Dahun Shin, Jinseok Chung, Namhoon Lee</div>
<div class="paper-venue">ICML 2023 Workshop on Federated Learning and Analytics in Practice</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://sites.google.com/view/aihci/papers" target="_blank">
Semi-Supervised Concept Bottleneck Models
</a>
</div>
<div class="paper-authors">Jeeon Bae, Sungbin Shin, Namhoon Lee</div>
<div class="paper-venue">ICML 2023 Workshop on Artificial Intelligence and Human-Computer Interaction</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://openreview.net/forum?id=IcDTYTI0Nx" target="_blank">
Almost Sure Last Iterate Convergence of Sharpness-Aware Minimization
</a>
</div>
<div class="paper-authors">Kyungchun Nam, Jinseok Chung, Namhoon Lee</div>
<div class="paper-venue">ICLR 2023 Tiny Papers</div>
</div>
<!-- ===== Previous ===== -->
<h3 class="year-divider">Previous</h3>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/2110.14678" target="_blank">
Meta-Learning Sparse Implicit Neural Representations
</a>
</div>
<div class="paper-authors">Jaeho Lee*, Jihoon Tack*, Namhoon Lee, Jinwoo Shin</div>
<div class="paper-venue">NeurIPS 2021; SNN 2021</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/2003.11316" target="_blank">
Understanding the Effects of Data Parallelism and Sparsity on Neural Network Training
</a>
</div>
<div class="paper-authors">Namhoon Lee, Thalaiyasingam Ajanthan, Philip H. S. Torr, Martin Jaggi</div>
<div class="paper-venue">ICLR 2021</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://sites.google.com/view/sedl-workshop" target="_blank">
Optimal Mini-Batch Size for Stochastic Gradient Methods
</a>
</div>
<div class="paper-authors">Namhoon Lee, Philip H. S. Torr, Richard Hartley</div>
<div class="paper-venue">ICLR 2021 Workshop on Science and Engineering of Deep Learning</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://ora.ox.ac.uk/objects/uuid:000e9d44-0229-48a3-84b0-dc17a8e96ccf" target="_blank">
Toward Efficient Deep Learning with Sparse Neural Networks
</a>
</div>
<div class="paper-authors">Namhoon Lee</div>
<div class="paper-venue">Ph.D. Thesis, University of Oxford</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/1906.06307" target="_blank">
A Signal Propagation Perspective for Pruning Neural Networks at Initialization
</a>
</div>
<div class="paper-authors">Namhoon Lee, Thalaiyasingam Ajanthan, Stephen Gould, Philip H. S. Torr</div>
<div class="paper-venue">ICLR 2020 <span class="spotlight">(Spotlight)</span></div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/2003.11316" target="_blank">
Data Parallelism in Training Sparse Neural Networks
</a>
</div>
<div class="paper-authors">Namhoon Lee, Philip H. S. Torr, Martin Jaggi</div>
<div class="paper-venue">ICLR 2020 Workshop on Practical ML</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/1810.02340" target="_blank">
SNIP: Single-shot Network Pruning based on Connection Sensitivity
</a>
</div>
<div class="paper-authors">Namhoon Lee, Thalaiyasingam Ajanthan, Philip H. S. Torr</div>
<div class="paper-venue">ICLR 2019</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/1804.02391" target="_blank">
Learn to Pay Attention
</a>
</div>
<div class="paper-authors">Saumya Jetley, Nicholas Lord, Namhoon Lee, Philip H. S. Torr</div>
<div class="paper-venue">ICLR 2018</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://link.springer.com/article/10.1007/s11263-018-1077-3" target="_blank">
Synthesizing a Scene-Specific Pedestrian Detector and Pose Estimator for Static Video Surveillance
</a>
</div>
<div class="paper-authors">
Hironori Hattori*, Namhoon Lee*, Vishnu N. Boddeti, Fares Beainy,
Kris M. Kitani, Takeo Kanade
</div>
<div class="paper-venue">IJCV 2018</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/1704.04394" target="_blank">
DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents
</a>
</div>
<div class="paper-authors">Namhoon Lee, Wongun Choi, Paul Vernaza, Christopher B. Choy, Philip H. S. Torr, Manmohan Chandraker</div>
<div class="paper-venue">CVPR 2017 <span class="spotlight">(Spotlight)</span></div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://arxiv.org/abs/1604.01431" target="_blank">
Forecasting Interactive Dynamics of Pedestrians with Fictitious Play
</a>
</div>
<div class="paper-authors">Wei-Chiu Ma, De-An Huang, Namhoon Lee, Kris M. Kitani</div>
<div class="paper-venue">CVPR 2017</div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://namhoonlee.github.io/doc/LK_WACV2016.pdf" target="_blank">
Predicting Wide Receiver Trajectories in American Football
</a>
</div>
<div class="paper-authors">Namhoon Lee, Kris M. Kitani</div>
<div class="paper-venue">WACV 2016 <span class="spotlight">(Oral)</span></div>
</div>
<div class="paper">
<div class="paper-title">
<a href="https://namhoonlee.github.io/doc/namhoonlee_msthesis2015_final.pdf" target="_blank">
Modeling of Dynamic Environments for Visual Forecasting of American Football Plays
</a>
</div>
<div class="paper-authors">Namhoon Lee (committee: Kris M. Kitani, Martial Hebert, Sebastian Scherer)</div>
<div class="paper-venue">M.S. Thesis, Carnegie Mellon University, Dec 2015</div>
</div>
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