Park, Sejun

23 publications

ICML 2025 Floating-Point Neural Networks Can Represent Almost All Floating-Point Functions Geonho Hwang, Yeachan Park, Wonyeol Lee, Sejun Park

ICML 2025 Minimum Width for Universal Approximation Using Squashable Activation Functions Jonghyun Shin, Namjun Kim, Geonho Hwang, Sejun Park

NeurIPS 2024 A Kernel Perspective on Distillation-Based Collaborative Learning Sejun Park, Kihun Hong, Ganguk Hwang

ICLR 2024 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

ICLR 2023 Guiding Energy-Based Models via Contrastive Latent Variables Hankook Lee, Jongheon Jeong, Sejun Park, Jinwoo Shin

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

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

ICML 2023 Towards Understanding Ensemble Distillation in Federated Learning Sejun Park, Kihun Hong, Ganguk Hwang

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

NeurIPSW 2022 Neural Networks Efficiently Learn Low-Dimensional Representations with SGD Alireza Mousavi-Hosseini, Sejun Park, Manuela Girotti, Ioannis Mitliagkas, Murat A Erdogdu

ICLR 2021 Layer-Adaptive Sparsity for the Magnitude-Based Pruning Jaeho Lee, Sejun Park, Sangwoo Mo, Sungsoo Ahn, Jinwoo Shin

ICLR 2021 Minimum Width for Universal Approximation Sejun Park, Chulhee Yun, Jaeho Lee, Jinwoo Shin

COLT 2021 Provable Memorization via Deep Neural Networks Using Sub-Linear Parameters Sejun Park, Jaeho Lee, Chulhee Yun, Jinwoo Shin

ICMLW 2021 SmoothMix: Training Confidence-Calibrated Smoothed Classifiers for Certified Adversarial Robustness Jongheon Jeong, Sejun Park, Minkyu Kim, Heung-Chang Lee, Doguk Kim, Jinwoo Shin

NeurIPS 2021 SmoothMix: Training Confidence-Calibrated Smoothed Classifiers for Certified Robustness Jongheon Jeong, Sejun Park, Minkyu Kim, Heung-Chang Lee, Do-Guk Kim, Jinwoo Shin

NeurIPS 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

NeurIPS 2020 Learning Bounds for Risk-Sensitive Learning Jaeho Lee, Sejun Park, Jinwoo Shin

ICLR 2020 Lookahead: A Far-Sighted Alternative of Magnitude-Based Pruning Sejun Park, Jaeho Lee, Sangwoo Mo, Jinwoo Shin

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

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

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

NeurIPS 2015 Minimum Weight Perfect Matching via Blossom Belief Propagation Sung-Soo Ahn, Sejun Park, Michael Chertkov, Jinwoo Shin