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2020 – today
- 2024
[j6]Yeachan Park
, Geonho Hwang, Wonyeol Lee, Sejun Park:
Expressive power of ReLU and step networks under floating-point operations. Neural Networks 175: 106297 (2024)- [j5]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): 4701-4712 (2024) - [c28]Namjun Kim, Chanho Min, Sejun Park:
Minimum width for universal approximation using ReLU networks on compact domain. ICLR 2024 - [c27]Sejun Park, Sanghyuk Chun, Wonyeol Lee:
What does automatic differentiation compute for neural networks? ICLR 2024 - [c26]Jaehyeon Baik, Sejun Park, Yunho Choi, Kyung-Joong Kim, Hosu Lee:
The Measurement Algorithm of the Center of Pressure Based on the Tactile Sensor. IWIS 2024: 1-4 - [c25]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, Sunghoi Hur:
Mechanical Stress Effects on Dielectric Leakage and Interconnection Integrity in 3D NAND Flash Memory. VLSI Technology and Circuits 2024: 1-2 - [c24]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, Bong-Tae Park, Sunghoi Hur:
Innovative Barrier Metal-Less Metal Gate Scheme Leading to Highly Reliable Cell Characteristics for 8th Generation 512Gb 3D NAND Flash Memory. VLSI Technology and Circuits 2024: 1-2 - [i21]Yeachan Park, Geonho Hwang, Wonyeol Lee, Sejun Park:
Expressive Power of ReLU and Step Networks under Floating-Point Operations. CoRR abs/2401.15121 (2024) - [i20]Geonho Hwang, Yeachan Park, Sejun Park:
On Expressive Power of Quantized Neural Networks under Fixed-Point Arithmetic. CoRR abs/2409.00297 (2024) - 2023
- [c23]Sejun Park, Ju Hyun Park, Sangmoon Lee:
Direct Demonstration-Based Imitation Learning and Control for Writing Task of Robot Manipulator. ICCE 2023: 1-3 - [c22]Sejun Park, Alain Pinsonneault, Warut Khern-am-nuai:
Status Regain and Validator Performance: Evidence from Blockchain Platform. ICIS 2023 - [c21]Alireza Mousavi Hosseini, Sejun Park, Manuela Girotti, Ioannis Mitliagkas, Murat A. Erdogdu:
Neural Networks Efficiently Learn Low-Dimensional Representations with SGD. ICLR 2023 - [c20]Hankook Lee, Jongheon Jeong, Sejun Park, Jinwoo Shin:
Guiding Energy-based Models via Contrastive Latent Variables. ICLR 2023 - [c19]Wonyeol Lee, Sejun Park, Alex Aiken:
On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters. ICML 2023: 19094-19140 - [c18]Sejun Park, Kihun Hong, Ganguk Hwang:
Towards Understanding Ensemble Distillation in Federated Learning. ICML 2023: 27132-27187 - [c17]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:
Process Improvements for 7th Generation 1Tb Quad-Level Cell 3D NAND Flash Memory in Mass Production. IMW 2023: 1-4 - [c16]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: 1-2 - [c15]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: 1-2 - [i19]Wonyeol Lee, Sejun Park, Alex Aiken:
On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters. CoRR abs/2301.13370 (2023) - [i18]Hankook Lee, Jongheon Jeong, Sejun Park, Jinwoo Shin:
Guiding Energy-based Models via Contrastive Latent Variables. CoRR abs/2303.03023 (2023) - [i17]Namjun Kim, Chanho Min, Sejun Park:
Minimum width for universal approximation using ReLU networks on compact domain. CoRR abs/2309.10402 (2023) - 2022
- [j4]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: 115061-115073 (2022) - [c14]Sejun Park, Umut Simsekli, Murat A. Erdogdu:
Generalization Bounds for Stochastic Gradient Descent via Localized $\varepsilon$-Covers. NeurIPS 2022 - [i16]Sejun Park, Umut Simsekli, Murat A. Erdogdu:
Generalization Bounds for Stochastic Gradient Descent via Localized ε-Covers. CoRR abs/2209.08951 (2022) - [i15]Alireza Mousavi Hosseini, Sejun Park, Manuela Girotti, Ioannis Mitliagkas, Murat A. Erdogdu:
Neural Networks Efficiently Learn Low-Dimensional Representations with SGD. CoRR abs/2209.14863 (2022) - 2021
- [c13]Sejun Park, Jaeho Lee, Chulhee Yun, Jinwoo Shin:
Provable Memorization via Deep Neural Networks using Sub-linear Parameters. COLT 2021: 3627-3661 - [c12]Jaeho Lee, Sejun Park, Sangwoo Mo, Sungsoo Ahn, Jinwoo Shin:
Layer-adaptive Sparsity for the Magnitude-based Pruning. ICLR 2021 - [c11]Sejun Park, Chulhee Yun, Jaeho Lee, Jinwoo Shin:
Minimum Width for Universal Approximation. ICLR 2021 - [c10]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: 30153-30168 - [i14]Jongheon Jeong, Sejun Park, Minkyu Kim, Heung-Chang Lee, Do-Guk Kim, Jinwoo Shin:
SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness. CoRR abs/2111.09277 (2021) - 2020
- [j3]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): 1428-1440 (2020) - [c9]Sejun Park, Jaeho Lee, Sangwoo Mo, Jinwoo Shin:
Lookahead: A Far-sighted Alternative of Magnitude-based Pruning. ICLR 2020 - [c8]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 - [c7]Jaeho Lee, Sejun Park, Jinwoo Shin:
Learning Bounds for Risk-sensitive Learning. NeurIPS 2020 - [i13]Sejun Park, Jaeho Lee, Sangwoo Mo, Jinwoo Shin:
Lookahead: a Far-Sighted Alternative of Magnitude-based Pruning. CoRR abs/2002.04809 (2020) - [i12]Jaeho Lee, Sejun Park, Jinwoo Shin:
Learning Bounds for Risk-sensitive Learning. CoRR abs/2006.08138 (2020) - [i11]Sejun Park, Chulhee Yun, Jaeho Lee, Jinwoo Shin:
Minimum Width for Universal Approximation. CoRR abs/2006.08859 (2020) - [i10]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 abs/2007.08844 (2020) - [i9]Jaeho Lee, Sejun Park, Sangwoo Mo, Sungsoo Ahn, Jinwoo Shin:
A Deeper Look at the Layerwise Sparsity of Magnitude-based Pruning. CoRR abs/2010.07611 (2020) - [i8]Sejun Park, Jaeho Lee, Chulhee Yun, Jinwoo Shin:
Provable Memorization via Deep Neural Networks using Sub-linear Parameters. CoRR abs/2010.13363 (2020)
2010 – 2019
- 2019
- [c6]Sejun Park, Eunho Yang, Se-Young Yun, Jinwoo Shin:
Spectral Approximate Inference. ICML 2019: 5052-5061 - [i7]Sejun Park, Eunho Yang, Se-Young Yun, Jinwoo Shin:
Spectral Approximate Inference. CoRR abs/1905.05348 (2019) - 2018
- [j2]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): 1471-1480 (2018) - [c5]Sejun Park, Deepjyoti Deka, Michael Chertkov:
Learning in Power Distribution Grids under Correlated Injections. ACSSC 2018: 1863-1868 - [i6]Sejun Park, Deepjyoti Deka, Scott Backhaus, Michael Chertkov:
Learning with End-Users in Distribution Grids: Topology and Parameter Estimation. CoRR abs/1803.04812 (2018) - 2017
- [j1]Sejun Park, Jinwoo Shin:
Convergence and Correctness of Max-Product Belief Propagation for Linear Programming. SIAM J. Discret. Math. 31(3): 2228-2246 (2017) - [c4]Sejun Park, Yunhun Jang, Andreas Galanis, Jinwoo Shin, Daniel Stefankovic, Eric Vigoda:
Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models. AISTATS 2017: 440-449 - [i5]Sejun Park, Eunho Yang, Jinwoo Shin:
Sequential Local Learning for Latent Graphical Models. CoRR abs/1703.04082 (2017) - [i4]Sejun Park, Yunhun Jang, Andreas Galanis, Jinwoo Shin, Daniel Stefankovic, Eric Vigoda:
Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models. CoRR abs/1704.02232 (2017) - [i3]Sejun Park, Deepjyoti Deka, Michael Chertkov:
Exact Topology and Parameter Estimation in Distribution Grids with Minimal Observability. CoRR abs/1710.10727 (2017) - 2015
- [c3]Inho Cho, Soya Park, Sejun Park, Dongsu Han, Jinwoo Shin:
Practical message-passing framework for large-scale combinatorial optimization. IEEE BigData 2015: 24-31 - [c2]Sungsoo Ahn, Sejun Park, Michael Chertkov, Jinwoo Shin:
Minimum Weight Perfect Matching via Blossom Belief Propagation. NIPS 2015: 1288-1296 - [c1]Sejun Park, Jinwoo Shin:
Max-Product Belief Propagation for Linear Programming: Applications to Combinatorial Optimization. UAI 2015: 662-671 - [i2]Sungsoo Ahn, Sejun Park, Michael Chertkov, Jinwoo Shin:
Minimum Weight Perfect Matching via Blossom Belief Propagation. CoRR abs/1509.06849 (2015) - 2014
- [i1]Sejun Park, Jinwoo Shin:
Max-Product Belief Propagation for Linear Programming: Convergence and Correctness. CoRR abs/1412.4972 (2014)
Coauthor Index
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