Sejun Park
19 papers · 2015–2025 · 5 conferences · across top CS/AI conferences
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knowledge distillation
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graph matching
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function approximation
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semi-supervised learning
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belief propagation
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automatic differentiation
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class imbalance
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Papers
Floating-Point Neural Networks Can Represent Almost All Floating-Point Functions
ICML 2025
Minimum Width for Universal Approximation using Squashable Activation Functions
ICML 2025
A Kernel Perspective on Distillation-based Collaborative Learning
NIPS 2024
Minimum width for universal approximation using ReLU networks on compact domain
ICLR 2024
What does automatic differentiation compute for neural networks?
ICLR 2024
On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters
ICML 2023
Neural Networks Efficiently Learn Low-Dimensional Representations with SGD
ICLR 2023
Towards Understanding Ensemble Distillation in Federated Learning
ICML 2023
Guiding Energy-based Models via Contrastive Latent Variables
ICLR 2023
Generalization Bounds for Stochastic Gradient Descent via Localized $\varepsilon$-Covers
NIPS 2022
Minimum Width for Universal Approximation
ICLR 2021
SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness
NIPS 2021
Provable Memorization via Deep Neural Networks using Sub-linear Parameters
COLT 2021
Layer-adaptive Sparsity for the Magnitude-based Pruning
ICLR 2021
Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning
NIPS 2020
Learning Bounds for Risk-sensitive Learning
NIPS 2020
Spectral Approximate Inference
ICML 2019
Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models
AISTATS 2017
Minimum Weight Perfect Matching via Blossom Belief Propagation
NIPS 2015