Sejun Park

According to our database, Sejun Park authored at least 33 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Expressive Power of ReLU and Step Networks under Floating-Point Operations.

Yeachan Park, Geonho Hwang, Wonyeol Lee, Sejun Park

CoRR, 2024

2023

Minimum width for universal approximation using ReLU networks on compact domain.

Namjun Kim, Chanho Min, Sejun Park

CoRR, 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

Proceedings of the 2023 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits), 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

Proceedings of the 2023 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits), 2023

Process Improvements for 7^th 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

Proceedings of the IEEE International Memory Workshop, 2023

Towards Understanding Ensemble Distillation in Federated Learning.

Sejun Park, Kihun Hong, Ganguk Hwang

Proceedings of the International Conference on Machine Learning, 2023

On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters.

Wonyeol Lee, Sejun Park, Alex Aiken

Proceedings of the International Conference on Machine Learning, 2023

Guiding Energy-based Models via Contrastive Latent Variables.

Hankook Lee, Jongheon Jeong, Sejun Park, Jinwoo Shin

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Neural Networks Efficiently Learn Low-Dimensional Representations with SGD.

Alireza Mousavi Hosseini, Sejun Park, Manuela Girotti, Ioannis Mitliagkas, Murat A. Erdogdu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Direct Demonstration-Based Imitation Learning and Control for Writing Task of Robot Manipulator.

Sejun Park, Ju Hyun Park, Sangmoon Lee

Proceedings of the IEEE International Conference on Consumer Electronics, 2023

2022

Generalization Bounds for Stochastic Gradient Descent via Localized ε-Covers.

Sejun Park, Umut Simsekli, Murat A. Erdogdu

CoRR, 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 $\varepsilon$-Covers.

Sejun Park, Umut Simsekli, Murat A. Erdogdu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness.

Jongheon Jeong, Sejun Park, Minkyu Kim, Heung-Chang Lee, Do-Guk Kim, Jinwoo Shin

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Minimum Width for Universal Approximation.

Sejun Park, Chulhee Yun, Jaeho Lee, Jinwoo Shin

Proceedings of the 9th International Conference on Learning Representations, 2021

Layer-adaptive Sparsity for the Magnitude-based Pruning.

Jaeho Lee, Sejun Park, Sangwoo Mo, Sungsoo Ahn, Jinwoo Shin

Proceedings of the 9th International Conference on Learning Representations, 2021

Provable Memorization via Deep Neural Networks using Sub-linear Parameters.

Sejun Park, Jaeho Lee, Chulhee Yun, Jinwoo Shin

Proceedings of the Conference on Learning Theory, 2021

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

A Deeper Look at the Layerwise Sparsity of Magnitude-based Pruning.

Jaeho Lee, Sejun Park, Sangwoo Mo, Sungsoo Ahn, Jinwoo Shin

CoRR, 2020

Learning Bounds for Risk-sensitive Learning.

Jaeho Lee, Sejun Park, Jinwoo Shin

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning.

Jaehyung Kim, Youngbum Hur, Sejun Park, Eunho Yang, Sung Ju Hwang, Jinwoo Shin

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Lookahead: A Far-sighted Alternative of Magnitude-based Pruning.

Sejun Park, Jaeho Lee, Sangwoo Mo, Jinwoo Shin

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Spectral Approximate Inference.

Sejun Park, Eunho Yang, Se-Young Yun, Jinwoo Shin

Proceedings of the 36th International Conference on Machine Learning, 2019

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

Learning in Power Distribution Grids under Correlated Injections.

Sejun Park, Deepjyoti Deka, Michael Chertkov

Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

2017

Convergence and Correctness of Max-Product Belief Propagation for Linear Programming.

Sejun Park, Jinwoo Shin

SIAM J. Discret. Math., 2017

Exact Topology and Parameter Estimation in Distribution Grids with Minimal Observability.

Sejun Park, Deepjyoti Deka, Michael Chertkov

CoRR, 2017

Sequential Local Learning for Latent Graphical Models.

Sejun Park, Eunho Yang, Jinwoo Shin

CoRR, 2017

Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models.

Sejun Park, Yunhun Jang, Andreas Galanis, Jinwoo Shin, Daniel Stefankovic, Eric Vigoda

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2015

Max-Product Belief Propagation for Linear Programming: Applications to Combinatorial Optimization.

Sejun Park, Jinwoo Shin

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Minimum Weight Perfect Matching via Blossom Belief Propagation.

Sungsoo Ahn, Sejun Park, Michael Chertkov, Jinwoo Shin

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Practical message-passing framework for large-scale combinatorial optimization.

Inho Cho, Soya Park, Sejun Park, Dongsu Han, Jinwoo Shin

Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

2014

Max-Product Belief Propagation for Linear Programming: Convergence and Correctness.

Sejun Park, Jinwoo Shin

CoRR, 2014