Sejun Park

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 46

Top Topics

Belief Propagation

Approximate Inference

Mass Production

Linear Programming

Top Venues

Publications

Seungyong Han, Sejun Park, Sangmoon Lee
Sampled-Data-Based Iterative Cost-Learning Model Predictive Control for T-S Fuzzy Systems. IEEE Trans. Syst. Man Cybern. Syst. 54 (8) (2024)
Namjun Kim, Chanho Min, Sejun Park
Minimum width for universal approximation using ReLU networks on compact domain. ICLR (2024)
Sejun Park, Sanghyuk Chun, Wonyeol Lee
What does automatic differentiation compute for neural networks? ICLR (2024)
Yeachan Park, Geonho Hwang, Wonyeol Lee, Sejun Park
Expressive power of ReLU and step networks under floating-point operations. Neural Networks 175 (2024)
Yeachan Park, Geonho Hwang, Wonyeol Lee, Sejun Park
Expressive Power of ReLU and Step Networks under Floating-Point Operations. CoRR (2024)
Sejun Park, Ju Hyun Park, Sangmoon Lee
Direct Demonstration-Based Imitation Learning and Control for Writing Task of Robot Manipulator. ICCE (2023)
Wonyeol Lee, Sejun Park, Alex Aiken
On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters. CoRR (2023)
Hankook Lee, Jongheon Jeong, Sejun Park, Jinwoo Shin
Guiding Energy-based Models via Contrastive Latent Variables. CoRR (2023)
Wonyeol Lee, Sejun Park, Alex Aiken
On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters. ICML (2023)
Changhwan Lee, Min-Tai Yu, Sejun Park, Hoki Lee, Bio Kim, Suhwan Lim, Jaeduk Lee, Sung-Hun Lee, Mincheol Park, Sujin Ahn, Sunghoi Hur
Novel Strategies for Highly Uniform and Reliable Cell Characteristics of 8th Generation 1Tb 3D-NAND Flash Memory. VLSI Technology and Circuits (2023)
Sejun Park, Alain Pinsonneault, Warut Khern-am-nuai
Status Regain and Validator Performance: Evidence from Blockchain Platform. ICIS (2023)
Sejun Park, Kihun Hong, Ganguk Hwang
Towards Understanding Ensemble Distillation in Federated Learning. ICML (2023)
Kyungmoon Kim, Yujeong Seo, Sejun Park, Woojae Jang, Dongho Yoo, Joonsung Lim, Il-Han Park, Jaeduk Lee, Kyungyoon Noh, Sujin Ahn, Sunghoi Hur
High Bit Cost Scalability and Reliable Cell Characteristics for 7th Generation 1Tb 4Bit/Cell 3D-NAND Flash. VLSI Technology and Circuits (2023)
Soochan Chung, Dong-Hyeon Ko, Joonsung Lim, Kyungmoon Kim, Sejie Takaki, Yujeong Seo, Byoungil Lee, Sejun Park, Jaeduk Lee, Kyungyoon Noh, Su Jin Ahn, Sunghoi Hur
Generation 1Tb Quad-Level Cell 3D NAND Flash Memory in Mass Production. IMW (2023)
Alireza Mousavi Hosseini, Sejun Park, Manuela Girotti, Ioannis Mitliagkas, Murat A. Erdogdu
Neural Networks Efficiently Learn Low-Dimensional Representations with SGD. ICLR (2023)
Namjun Kim, Chanho Min, Sejun Park
Minimum width for universal approximation using ReLU networks on compact domain. CoRR (2023)
Hankook Lee, Jongheon Jeong, Sejun Park, Jinwoo Shin
Guiding Energy-based Models via Contrastive Latent Variables. ICLR (2023)
Alireza Mousavi Hosseini, Sejun Park, Manuela Girotti, Ioannis Mitliagkas, Murat A. Erdogdu
Neural Networks Efficiently Learn Low-Dimensional Representations with SGD. CoRR (2022)
Sejun Park, Umut Simsekli, Murat A. Erdogdu
Generalization Bounds for Stochastic Gradient Descent via Localized $\varepsilon$-Covers. NeurIPS (2022)
Ki Joung Jang, Sejun Park, Junseok Kim, Youngkeun Yoon, Chung-Sup Kim, Young-Jun Chong, Ganguk Hwang
Path Loss Model Based on Machine Learning Using Multi-Dimensional Gaussian Process Regression. IEEE Access 10 (2022)
Sejun Park, Umut Simsekli, Murat A. Erdogdu
Generalization Bounds for Stochastic Gradient Descent via Localized ε-Covers. CoRR (2022)
Sejun Park, Chulhee Yun, Jaeho Lee, Jinwoo Shin
Minimum Width for Universal Approximation. ICLR (2021)
Jongheon Jeong, Sejun Park, Minkyu Kim, Heung-Chang Lee, Do-Guk Kim, Jinwoo Shin
SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness. CoRR (2021)
Jaeho Lee, Sejun Park, Sangwoo Mo, Sungsoo Ahn, Jinwoo Shin
Layer-adaptive Sparsity for the Magnitude-based Pruning. ICLR (2021)
Jongheon Jeong, Sejun Park, Minkyu Kim, Heung-Chang Lee, Do-Guk Kim, Jinwoo Shin
SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness. NeurIPS (2021)
Sejun Park, Jaeho Lee, Chulhee Yun, Jinwoo Shin
Provable Memorization via Deep Neural Networks using Sub-linear Parameters. COLT (2021)
Jaeho Lee, Sejun Park, Jinwoo Shin
Learning Bounds for Risk-sensitive Learning. CoRR (2020)
Jaehyung Kim, Youngbum Hur, Sejun Park, Eunho Yang, Sung Ju Hwang, Jinwoo Shin
Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning. NeurIPS (2020)
Jaehyung Kim, Youngbum Hur, Sejun Park, Eunho Yang, Sung Ju Hwang, Jinwoo Shin
Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning. CoRR (2020)
Sejun Park, Jaeho Lee, Chulhee Yun, Jinwoo Shin
Provable Memorization via Deep Neural Networks using Sub-linear Parameters. CoRR (2020)
Jaeho Lee, Sejun Park, Sangwoo Mo, Sungsoo Ahn, Jinwoo Shin
A Deeper Look at the Layerwise Sparsity of Magnitude-based Pruning. CoRR (2020)
Jaeho Lee, Sejun Park, Jinwoo Shin
Learning Bounds for Risk-sensitive Learning. NeurIPS (2020)
Sejun Park, Chulhee Yun, Jaeho Lee, Jinwoo Shin
Minimum Width for Universal Approximation. CoRR (2020)
Sejun Park, Deepjyoti Deka, Scott Backhaus, Michael Chertkov
Learning With End-Users in Distribution Grids: Topology and Parameter Estimation. IEEE Trans. Control. Netw. Syst. 7 (3) (2020)
Sejun Park, Jaeho Lee, Sangwoo Mo, Jinwoo Shin
Lookahead: a Far-Sighted Alternative of Magnitude-based Pruning. CoRR (2020)
Sejun Park, Jaeho Lee, Sangwoo Mo, Jinwoo Shin
Lookahead: A Far-sighted Alternative of Magnitude-based Pruning. ICLR (2020)
Sejun Park, Eunho Yang, Se-Young Yun, Jinwoo Shin
Spectral Approximate Inference. ICML (2019)
Sejun Park, Eunho Yang, Se-Young Yun, Jinwoo Shin
Spectral Approximate Inference. CoRR (2019)
Sungsoo Ahn, Michael Chertkov, Andrew E. Gelfand, Sejun Park, Jinwoo Shin
Maximum Weight Matching Using Odd-Sized Cycles: Max-Product Belief Propagation and Half-Integrality. IEEE Trans. Inf. Theory 64 (3) (2018)
Sejun Park, Deepjyoti Deka, Michael Chertkov
Learning in Power Distribution Grids under Correlated Injections. ACSSC (2018)
Sejun Park, Deepjyoti Deka, Scott Backhaus, Michael Chertkov
Learning with End-Users in Distribution Grids: Topology and Parameter Estimation. CoRR (2018)
Sejun Park, Jinwoo Shin
Convergence and Correctness of Max-Product Belief Propagation for Linear Programming. SIAM J. Discret. Math. 31 (3) (2017)
Sejun Park, Eunho Yang, Jinwoo Shin
Sequential Local Learning for Latent Graphical Models. CoRR (2017)
Sejun Park, Yunhun Jang, Andreas Galanis, Jinwoo Shin, Daniel Stefankovic, Eric Vigoda
Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models. AISTATS (2017)
Sejun Park, Deepjyoti Deka, Michael Chertkov
Exact Topology and Parameter Estimation in Distribution Grids with Minimal Observability. CoRR (2017)
Sejun Park, Yunhun Jang, Andreas Galanis, Jinwoo Shin, Daniel Stefankovic, Eric Vigoda
Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models. CoRR (2017)
Sejun Park, Jinwoo Shin
Max-Product Belief Propagation for Linear Programming: Applications to Combinatorial Optimization. UAI (2015)
Sungsoo Ahn, Sejun Park, Michael Chertkov, Jinwoo Shin
Minimum Weight Perfect Matching via Blossom Belief Propagation. CoRR (2015)
Inho Cho, Soya Park, Sejun Park, Dongsu Han, Jinwoo Shin
Practical message-passing framework for large-scale combinatorial optimization. IEEE BigData (2015)
Sungsoo Ahn, Sejun Park, Michael Chertkov, Jinwoo Shin
Minimum Weight Perfect Matching via Blossom Belief Propagation. NIPS (2015)
Sejun Park, Jinwoo Shin
Max-Product Belief Propagation for Linear Programming: Convergence and Correctness. CoRR (2014)