Sejun Park

Orcid: 0000-0003-1580-5664

According to our database1, Sejun Park authored at least 41 papers between 2014 and 2024.

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Bibliography

2024
Sampled-Data-Based Iterative Cost-Learning Model Predictive Control for T-S Fuzzy Systems.
IEEE Trans. Syst. Man Cybern. Syst., August, 2024

Expressive power of ReLU and step networks under floating-point operations.
Neural Networks, 2024

A Kernel Perspective on Distillation-based Collaborative Learning.
CoRR, 2024

On Expressive Power of Quantized Neural Networks under Fixed-Point Arithmetic.
CoRR, 2024

Innovative Barrier Metal-Less Metal Gate Scheme Leading to Highly Reliable Cell Characteristics for 8th Generation 512Gb 3D NAND Flash Memory.
Proceedings of the IEEE Symposium on VLSI Technology and Circuits 2024, 2024

Mechanical Stress Effects on Dielectric Leakage and Interconnection Integrity in 3D NAND Flash Memory.
Proceedings of the IEEE Symposium on VLSI Technology and Circuits 2024, 2024

The Measurement Algorithm of the Center of Pressure Based on the Tactile Sensor.
Proceedings of the International Workshop on Intelligent Systems, 2024

What does automatic differentiation compute for neural networks?
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Minimum width for universal approximation using ReLU networks on compact domain.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Novel Strategies for Highly Uniform and Reliable Cell Characteristics of 8th Generation 1Tb 3D-NAND Flash Memory.
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.
Proceedings of the 2023 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits), 2023

Process Improvements for 7<sup>th</sup> Generation 1Tb Quad-Level Cell 3D NAND Flash Memory in Mass Production.
Proceedings of the IEEE International Memory Workshop, 2023

Towards Understanding Ensemble Distillation in Federated Learning.
Proceedings of the International Conference on Machine Learning, 2023

On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters.
Proceedings of the International Conference on Machine Learning, 2023

Guiding Energy-based Models via Contrastive Latent Variables.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Neural Networks Efficiently Learn Low-Dimensional Representations with SGD.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Status Regain and Validator Performance: Evidence from Blockchain Platform.
Proceedings of the 44th International Conference on Information Systems, 2023

Direct Demonstration-Based Imitation Learning and Control for Writing Task of Robot Manipulator.
Proceedings of the IEEE International Conference on Consumer Electronics, 2023

2022
Generalization Bounds for Stochastic Gradient Descent via Localized ε-Covers.
CoRR, 2022

Path Loss Model Based on Machine Learning Using Multi-Dimensional Gaussian Process Regression.
IEEE Access, 2022

Generalization Bounds for Stochastic Gradient Descent via Localized $\varepsilon$-Covers.
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.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Minimum Width for Universal Approximation.
Proceedings of the 9th International Conference on Learning Representations, 2021

Layer-adaptive Sparsity for the Magnitude-based Pruning.
Proceedings of the 9th International Conference on Learning Representations, 2021

Provable Memorization via Deep Neural Networks using Sub-linear Parameters.
Proceedings of the Conference on Learning Theory, 2021

2020
Learning With End-Users in Distribution Grids: Topology and Parameter Estimation.
IEEE Trans. Control. Netw. Syst., 2020

A Deeper Look at the Layerwise Sparsity of Magnitude-based Pruning.
CoRR, 2020

Learning Bounds for Risk-sensitive Learning.
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.
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.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Spectral Approximate Inference.
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.
IEEE Trans. Inf. Theory, 2018

Learning in Power Distribution Grids under Correlated Injections.
Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

2017
Convergence and Correctness of Max-Product Belief Propagation for Linear Programming.
SIAM J. Discret. Math., 2017

Exact Topology and Parameter Estimation in Distribution Grids with Minimal Observability.
CoRR, 2017

Sequential Local Learning for Latent Graphical Models.
CoRR, 2017

Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2015
Max-Product Belief Propagation for Linear Programming: Applications to Combinatorial Optimization.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Minimum Weight Perfect Matching via Blossom Belief Propagation.
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.
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.
CoRR, 2014


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