Saerom Park

Orcid: 0000-0002-2687-7105

According to our database1, Saerom Park authored at least 15 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
The SaTML '24 CNN Interpretability Competition: New Innovations for Concept-Level Interpretability.
CoRR, 2024

Fair Sampling in Diffusion Models through Switching Mechanism.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Efficient homomorphic encryption framework for privacy-preserving regression.
Appl. Intell., May, 2023

Efficient differentially private kernel support vector classifier for multi-class classification.
Inf. Sci., 2023

2022
Efficient Generation of Program Execution Hash.
IEEE Access, 2022

Fairness Audit of Machine Learning Models with Confidential Computing.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Privacy-Preserving Fair Learning of Support Vector Machine with Homomorphic Encryption.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

2021
Stability Analysis of Denoising Autoencoders Based on Dynamical Projection System.
IEEE Trans. Knowl. Data Eng., 2021

2020
HE-Friendly Algorithm for Privacy-Preserving SVM Training.
IEEE Access, 2020

Lipschitz-Certifiable Training with a Tight Outer Bound.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Semi-supervised distributed representations of documents for sentiment analysis.
Neural Networks, 2019

Learning of indiscriminate distributions of document embeddings for domain adaptation.
Intell. Data Anal., 2019

Security-preserving Support Vector Machine with Fully Homomorphic Encryption.
Proceedings of the Workshop on Artificial Intelligence Safety 2019 co-located with the Thirty-Third AAAI Conference on Artificial Intelligence 2019 (AAAI-19), 2019

2018
Learning representative exemplars using one-class Gaussian process regression.
Pattern Recognit., 2018

Information-Based Boundary Equilibrium Generative Adversarial Networks with Interpretable Representation Learning.
Comput. Intell. Neurosci., 2018


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