Max-Product Belief Propagation for Linear Programming: Convergence and Correctness. - Sejun Park; Jinwoo Shin (CoRR, 2014)

Practical message-passing framework for large-scale combinatorial optimization. - Inho Cho; Soya Park; Sejun Park; Dongsu Han; Jinwoo Shin (IEEE BigData, 2015)

Minimum Weight Perfect Matching via Blossom Belief Propagation. - Sungsoo Ahn; Sejun Park; Michael Chertkov; Jinwoo Shin (NIPS, 2015)

Max-Product Belief Propagation for Linear Programming: Applications to Combinatorial Optimization. - Sejun Park; Jinwoo Shin (UAI, 2015)

Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models. - Sejun Park; Yunhun Jang; Andreas Galanis; Jinwoo Shin; Daniel Stefankovic; Eric Vigoda (AISTATS, 2017)

Sequential Local Learning for Latent Graphical Models. - Sejun Park; Eunho Yang; Jinwoo Shin (CoRR, 2017)

Exact Topology and Parameter Estimation in Distribution Grids with Minimal Observability. - Sejun Park; Deepjyoti Deka; Michael Chertkov (CoRR, 2017)

Convergence and Correctness of Max-Product Belief Propagation for Linear Programming. - Sejun Park; Jinwoo Shin (SIAM J. Discret. Math., 2017)

Learning in Power Distribution Grids under Correlated Injections. - Sejun Park; Deepjyoti Deka; Michael Chertkov (ACSSC, 2018)

Maximum Weight Matching Using Odd-Sized Cycles: Max-Product Belief Propagation and Half-Integrality. - Sungsoo Ahn; Michael Chertkov; Andrew E. Gelfand; Sejun Park; Jinwoo Shin (IEEE Trans. Inf. Theory, 2018)

Spectral Approximate Inference. - Sejun Park; Eunho Yang; Se-Young Yun; Jinwoo Shin (ICML, 2019)

Lookahead: A Far-sighted Alternative of Magnitude-based Pruning. - Sejun Park; Jaeho Lee 001; Sangwoo Mo; Jinwoo Shin (ICLR, 2020)

Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning. - Jaehyung Kim 001; Youngbum Hur; Sejun Park; Eunho Yang; Sung Ju Hwang; Jinwoo Shin (NeurIPS, 2020)

Learning Bounds for Risk-sensitive Learning. - Jaeho Lee 001; Sejun Park; Jinwoo Shin (NeurIPS, 2020)

A Deeper Look at the Layerwise Sparsity of Magnitude-based Pruning. - Jaeho Lee 001; Sejun Park; Sangwoo Mo; Sungsoo Ahn; Jinwoo Shin (CoRR, 2020)

Learning With End-Users in Distribution Grids: Topology and Parameter Estimation. - Sejun Park; Deepjyoti Deka; Scott Backhaus; Michael Chertkov (IEEE Trans. Control. Netw. Syst., 2020)

Provable Memorization via Deep Neural Networks using Sub-linear Parameters. - Sejun Park; Jaeho Lee 001; Chulhee Yun; Jinwoo Shin (COLT, 2021)

Layer-adaptive Sparsity for the Magnitude-based Pruning. - Jaeho Lee 001; Sejun Park; Sangwoo Mo; Sungsoo Ahn; Jinwoo Shin (ICLR, 2021)

Minimum Width for Universal Approximation. - Sejun Park; Chulhee Yun; Jaeho Lee 001; Jinwoo Shin (ICLR, 2021)

SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness. - Jongheon Jeong; Sejun Park; Minkyu Kim 004; Heung-Chang Lee; Do-Guk Kim; Jinwoo Shin (NeurIPS, 2021)

Generalization Bounds for Stochastic Gradient Descent via Localized $ varepsilon$-Covers. - Sejun Park; Umut Simsekli; Murat A. Erdogdu (NeurIPS, 2022)

Path Loss Model Based on Machine Learning Using Multi-Dimensional Gaussian Process Regression. - Ki Joung Jang; Sejun Park; Junseok Kim; Youngkeun Yoon; Chung-Sup Kim; Young-Jun Chong; Ganguk Hwang (IEEE Access, 2022)

Generalization Bounds for Stochastic Gradient Descent via Localized ε-Covers. - Sejun Park; Umut Simsekli; Murat A. Erdogdu (CoRR, 2022)

Direct Demonstration-Based Imitation Learning and Control for Writing Task of Robot Manipulator. - Sejun Park; Ju Hyun Park 001; Sangmoon Lee 001 (ICCE, 2023)

Status Regain and Validator Performance: Evidence from Blockchain Platform. - Sejun Park; Alain Pinsonneault; Warut Khern-am-nuai (ICIS, 2023)

Neural Networks Efficiently Learn Low-Dimensional Representations with SGD. - Alireza Mousavi Hosseini; Sejun Park; Manuela Girotti; Ioannis Mitliagkas; Murat A. Erdogdu (ICLR, 2023)

Guiding Energy-based Models via Contrastive Latent Variables. - Hankook Lee; Jongheon Jeong; Sejun Park; Jinwoo Shin (ICLR, 2023)

On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters. - Wonyeol Lee 001; Sejun Park; Alex Aiken (ICML, 2023)

Towards Understanding Ensemble Distillation in Federated Learning. - Sejun Park; Kihun Hong; Ganguk Hwang (ICML, 2023)

Process Improvements for 7th Generation 1Tb Quad-Level Cell 3D NAND Flash Memory in Mass Production. - Soochan Chung; Dong-Hyeon Ko; Joonsung Lim; Kyungmoon Kim; Sejie Takaki; Yujeong Seo; Byoungil Lee; Sejun Park; Jaeduk Lee; Kyungyoon Noh; Sujin Ahn; Sunghoi Hur (IMW, 2023)

High Bit Cost Scalability and Reliable Cell Characteristics for 7th Generation 1Tb 4Bit/Cell 3D-NAND Flash. - Kyungmoon Kim; Yujeong Seo; Sejun Park; Woojae Jang; Dongho Yoo; Joonsung Lim; Il-Han Park; Jaeduk Lee; Kyungyoon Noh; Sujin Ahn; Sunghoi Hur (VLSI Technology and Circuits, 2023)

Novel Strategies for Highly Uniform and Reliable Cell Characteristics of 8th Generation 1Tb 3D-NAND Flash Memory. - Changhwan Lee; Min-Tai Yu; Sejun Park; Hoki Lee; Bio Kim; Suhwan Lim; Jaeduk Lee; Sung-Hun Lee; Mincheol Park; Sujin Ahn; Sunghoi Hur (VLSI Technology and Circuits, 2023)

Minimum width for universal approximation using ReLU networks on compact domain. - Namjun Kim; Chanho Min; Sejun Park (ICLR, 2024)

What does automatic differentiation compute for neural networks? - Sejun Park; Sanghyuk Chun; Wonyeol Lee 001 (ICLR, 2024)

The Measurement Algorithm of the Center of Pressure Based on the Tactile Sensor. - Jaehyeon Baik; Sejun Park; Yunho Choi; Kyung-Joong Kim 001; Hosu Lee (IWIS, 2024)

A Kernel Perspective on Distillation-based Collaborative Learning. - Sejun Park; Kihun Hong; Ganguk Hwang (NeurIPS, 2024)

Mechanical Stress Effects on Dielectric Leakage and Interconnection Integrity in 3D NAND Flash Memory. - Sehoon Lee; Jieun Lee; Sungpil Jang; Sujeong Kim; Choelgyu Kim; Narae Jeong Sae-Jin Kim; Jisoo Kang; Juhee Hong; Dong-Kyu Kim; Junhee Lim; Sejun Park; Seungwan Hong; et al. (VLSI Technology and Circuits, 2024)

Innovative Barrier Metal-Less Metal Gate Scheme Leading to Highly Reliable Cell Characteristics for 8th Generation 512Gb 3D NAND Flash Memory. - Hang-Ah Park; Sejun Park; Min-Tai Yu; Ye-Chan Kim; Cheon Ho Park; Jung Hoon Lee; Jun Eon Jin; Dawoon Jeung; Hauk Han; Tai-Soo Lim; Min-Kyu Jeong; Mincheol Park; et al. (VLSI Technology and Circuits, 2024)

On Expressive Power of Quantized Neural Networks under Fixed-Point Arithmetic. - Geonho Hwang; Yeachan Park; Sejun Park (CoRR, 2024)

IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs. - Sejun Park; Joo Young Park; Hyunwoo Park (CoRR, 2024)

Expressive power of ReLU and step networks under floating-point operations. - Yeachan Park; Geonho Hwang; Wonyeol Lee 001; Sejun Park (Neural Networks, 2024)

Sampled-Data-Based Iterative Cost-Learning Model Predictive Control for T-S Fuzzy Systems. - Seungyong Han; Sejun Park; Sangmoon Lee 001 (IEEE Trans. Syst. Man Cybern. Syst., 2024)

Floating-Point Neural Networks are Provably Robust Universal Approximators. - Geonho Hwang; Wonyeol Lee 001; Yeachan Park; Sejun Park; Feras Saad (CAV (2), 2025)

Development of Innovative Self-Aligned SSL Mold (SASM) Scheme with Remarkable Reduction of Chip Size. - Junyoung Lee; Minkyu Jeong; Sejun Park; Joonam Kim; Joonghyeob Shin; Jongyoon Choi; Jihoon Choi; Byungsoo Kim; Yujeong Seo; Gilsung Lee; Dongsik Lee; Joon Kim; et al. (IMW, 2025)

First Demonstration of Threshold Voltage Modeling in Multi-Hole V-NAND Flash Architecture with Noncircular Channel Hole Profiles. - Chanyang Park; Min-Kyu Jeong; Taein Lee; Sejun Park; Jung Hoon Lee; Yujin Lee; Seungwan Hong; Sunghoi Hur (IMW, 2025)

Innovative V-NAND Flash Structure with Dual Trap Layer for Future Generations of Multi-Bit Device. - Jeongyoon Yeo; Joonsung Kim; Younghwan Son; Taein Lee; Sejun Park; Min-Kyu Jeong; Jung Hoon Lee; Suk-Kang Sung; Dongku Kang; Seungwan Hong; Sunghoi Hur (IMW, 2025)

Minimum width for universal approximation using squashable activation functions. - Jonghyun Shin; Namjun Kim; Geonho Hwang; Sejun Park (CoRR, 2025)

Deep Latent Variable Model based Vertical Federated Learning with Flexible Alignment and Labeling Scenarios. - Kihun Hong; Sejun Park; Ganguk Hwang (CoRR, 2025)