Jaewook Lee

Orcid: 0000-0001-5720-8337

Affiliations:
  • Seoul National University, Department of Industrial Engineering, South Korea
  • Pohang University of Science and Technology (POSTECH), Department of Industrial and Management Engineering, South Korea (2001 - 2012)
  • Cornell University, Ithaca, NY, USA (PhD 1999)


According to our database1, Jaewook Lee authored at least 114 papers between 2000 and 2025.

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

Timeline

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Bibliography

2025
Improving the utility of differentially private clustering through dynamical processing.
Pattern Recognit., 2025

2024
Unraveling the MEV enigma: ABI-free detection model using Graph Neural Networks.
Future Gener. Comput. Syst., 2024

Privacy-preserving inference resistant to model extraction attacks.
Expert Syst. Appl., 2024

Evaluating practical adversarial robustness of fault diagnosis systems via spectrogram-aware ensemble method.
Eng. Appl. Artif. Intell., 2024

Leveraging Priors via Diffusion Bridge for Time Series Generation.
CoRR, 2024

Are Self-Attentions Effective for Time Series Forecasting?
CoRR, 2024

Impact of EIP-4844 on Ethereum: Consensus Security, Ethereum Usage, Rollup Transaction Dynamics, and Blob Gas Fee Markets.
CoRR, 2024

Fair Sampling in Diffusion Models through Switching Mechanism.
CoRR, 2024

Transparent Object Depth Reconstruction Framework for Mixed Scenes with Transparent and Opaque Objects.
Proceedings of the 21st International Conference on Ubiquitous Robots, 2024

A Methodology of Stable 6-DoF Grasp Detection for Complex Shaped Object Using End-to-End Network.
Proceedings of the 21st International Conference on Ubiquitous Robots, 2024

In-Distribution Public Data Synthesis With Diffusion Models for Differentially Private Image Classification.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

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

2023
Bridged adversarial training.
Neural Networks, October, 2023

Fast sharpness-aware training for periodic time series classification and forecasting.
Appl. Soft Comput., September, 2023

Generating Transferable Adversarial Examples for Speech Classification.
Pattern Recognit., May, 2023

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

GradDiv: Adversarial Robustness of Randomized Neural Networks via Gradient Diversity Regularization.
IEEE Trans. Pattern Anal. Mach. Intell., 2023

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

Exploring the Effect of Multi-step Ascent in Sharpness-Aware Minimization.
CoRR, 2023

Stability Analysis of Sharpness-Aware Minimization.
CoRR, 2023

Exploring Diverse Feature Extractions for Adversarial Audio Detection.
IEEE Access, 2023

Fantastic Robustness Measures: The Secrets of Robust Generalization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fast and Differentially Private Fair Clustering.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Implicit Jacobian regularization weighted with impurity of probability output.
Proceedings of the International Conference on Machine Learning, 2023

Differentially Private Sharpness-Aware Training.
Proceedings of the International Conference on Machine Learning, 2023

2022
Variational cycle-consistent imputation adversarial networks for general missing patterns.
Pattern Recognit., 2022

Comment on Transferability and Input Transformation with Additive Noise.
CoRR, 2022

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

Compact class-conditional domain invariant learning for multi-class domain adaptation.
Pattern Recognit., 2021

A Survey on Security and Privacy in Blockchain-based Central Bank Digital Currencies.
J. Internet Serv. Inf. Secur., 2021

Atomic cross-chain settlement model for central banks digital currency.
Inf. Sci., 2021

Fair Clustering with Fair Correspondence Distribution.
Inf. Sci., 2021

Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Parameter-free HE-friendly Logistic Regression.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Understanding Catastrophic Overfitting in Single-step Adversarial Training.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Joint Transfer of Model Knowledge and Fairness Over Domains Using Wasserstein Distance.
IEEE Access, 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

An Empirical Study on Modeling and Prediction of Bitcoin Prices With Bayesian Neural Networks Based on Blockchain Information.
IEEE Access, 2018

2016
Active learning using transductive sparse Bayesian regression.
Inf. Sci., 2016

Nonparametric machine learning models for predicting the credit default swaps: An empirical study.
Expert Syst. Appl., 2016

Self-correcting ensemble using a latent consensus model.
Appl. Soft Comput., 2016

A general framework for building machine learning models for pricing american index options with no-arbitrage and its limitation.
Proceedings of the First Workshop on MIning DAta for financial applicationS (MIDAS 2016) co-located with the 2016 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2016), 2016

2015
Voronoi Cell-Based Clustering Using a Kernel Support.
IEEE Trans. Knowl. Data Eng., 2015

2014
Sentiment visualization and classification via semi-supervised nonlinear dimensionality reduction.
Pattern Recognit., 2014

Nonlinear Dynamic Projection for Noise Reduction of Dispersed Manifolds.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

Parametric models and non-parametric machine learning models for predicting option prices: Empirical comparison study over KOSPI 200 Index options.
Expert Syst. Appl., 2014

Improved churn prediction in telecommunication industry by analyzing a large network.
Expert Syst. Appl., 2014

Transductive Gaussian Processes with Applications to Object Pose Estimation.
Comput. J., 2014

2013
Tridiagonal implicit method to evaluate European and American options under infinite activity Lévy models.
J. Comput. Appl. Math., 2013

Probabilistic generative ranking method based on multi-support vector domain description.
Inf. Sci., 2013

2012
Multi-basin particle swarm intelligence method for optimal calibration of parametric Lévy models.
Expert Syst. Appl., 2012

Forecasting trends of high-frequency KOSPI200 index data using learning classifiers.
Expert Syst. Appl., 2012

Forecasting nonnegative option price distributions using Bayesian kernel methods.
Expert Syst. Appl., 2012

Transductive Bayesian regression via manifold learning of prior data structure.
Expert Syst. Appl., 2012

Sequential manifold learning for efficient churn prediction.
Expert Syst. Appl., 2012

Uniformly subsampled ensemble (USE) for churn management: Theory and implementation.
Expert Syst. Appl., 2012

A New Ensemble Model for Efficient Churn Prediction in Mobile Telecommunication.
Proceedings of the 45th Hawaii International International Conference on Systems Science (HICSS-45 2012), 2012

2011
Dynamic pattern denoising method using multi-basin system with kernels.
Pattern Recognit., 2011

Calibrating parametric exponential Lévy models to option market data by incorporating statistical moments priors.
Expert Syst. Appl., 2011

Predicting a distribution of implied volatilities for option pricing.
Expert Syst. Appl., 2011

2010
Dynamic Dissimilarity Measure for Support-Based Clustering.
IEEE Trans. Knowl. Data Eng., 2010

Fast support-based clustering method for large-scale problems.
Pattern Recognit., 2010

Improving memory-based collaborative filtering via similarity updating and prediction modulation.
Inf. Sci., 2010

A hybrid approach of goal programming for weapon systems selection.
Comput. Ind. Eng., 2010

2009
Constructing Sparse Kernel Machines Using Attractors.
IEEE Trans. Neural Networks, 2009

Prediction of credit delinquents using locally transductive multi-layer perceptron.
Neurocomputing, 2009

Support for seamless data exchanges between web services through information mapping analysis using kernel methods.
Expert Syst. Appl., 2009

User credit-based collaborative filtering.
Expert Syst. Appl., 2009

An iterative semi-explicit rating method for building collaborative recommender systems.
Expert Syst. Appl., 2009

Kernel-based Monte Carlo simulation for American option pricing.
Expert Syst. Appl., 2009

2008
A novel method for measuring semantic similarity for XML schema matching.
Expert Syst. Appl., 2008

Prediction of pricing and hedging errors for equity linked warrants with Gaussian process models.
Expert Syst. Appl., 2008

Simulations for American Option Pricing Under a Jump-Diffusion Model: Comparison Study between Kernel-Based and Regression-based Methods.
Proceedings of the Advances in Neural Networks, 2008

2007
Equilibrium-Based Support Vector Machine for Semisupervised Classification.
IEEE Trans. Neural Networks, 2007

Domain described support vector classifier for multi-classification problems.
Pattern Recognit., 2007

Clustering Based on Gaussian Processes.
Neural Comput., 2007

A novel three-phase trajectory informed search methodology for global optimization.
J. Glob. Optim., 2007

A quadratic string adapted barrier exploring method for locating transition states.
Comput. Phys. Commun., 2007

Approximate Sampling Method for Locally Linear Embedding.
Proceedings of the International Joint Conference on Neural Networks, 2007

2006
Frequency Insertion Strategy for Channel Assignment Problem.
Wirel. Networks, 2006

Dynamic Characterization of Cluster Structures for Robust and Inductive Support Vector Clustering.
IEEE Trans. Pattern Anal. Mach. Intell., 2006

A tandem clustering process for multimodal datasets.
Eur. J. Oper. Res., 2006

Local Volatility Function Approximation Using Reconstructed Radial Basis Function Networks.
Proceedings of the Advances in Neural Networks - ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28, 2006

Pseudo-density Estimation for Clustering with Gaussian Processes.
Proceedings of the Advances in Neural Networks - ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28, 2006

A Novel Learning Network for Option Pricing with Confidence Interval Information.
Proceedings of the Advances in Neural Networks - ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28, 2006

Support Vector Classifier Using Basin-Based Sampling for Security Assessment of Nonlinear Power and Control Systems.
Proceedings of the International Joint Conference on Neural Networks, 2006

A Novel Semi-Supervised Learning Methods Using Support Vector Domain Description.
Proceedings of the International Joint Conference on Neural Networks, 2006

2005
Pseudobasin of attraction for combinatorial dynamical systems: theory and its application to combinatorial optimization.
IEEE Trans. Circuits Syst. II Express Briefs, 2005

An Improved Cluster Labeling Method for Support Vector Clustering.
IEEE Trans. Pattern Anal. Mach. Intell., 2005

Classification-based collaborative filtering using market basket data.
Expert Syst. Appl., 2005

Solving Hard Local Minima Problems Using Basin Cells for Multilayer Perceptron Training.
Proceedings of the Advances in Neural Networks - ISNN 2005, Second International Symposium on Neural Networks, Chongqing, China, May 30, 2005

Coherent Risk Measure Using Feedfoward Neural Networks.
Proceedings of the Advances in Neural Networks - ISNN 2005, Second International Symposium on Neural Networks, Chongqing, China, May 30, 2005

Trajectory-Based Support Vector Multicategory Classifier.
Proceedings of the Advances in Neural Networks - ISNN 2005, Second International Symposium on Neural Networks, Chongqing, China, May 30, 2005

Estimating the Yield Curve Using Calibrated Radial Basis Function Networks.
Proceedings of the Advances in Neural Networks - ISNN 2005, Second International Symposium on Neural Networks, Chongqing, China, May 30, 2005

2004
A singular fixed-point homotopy method to locate the closest unstable equilibrium point for transient stability region estimate.
IEEE Trans. Circuits Syst. II Express Briefs, 2004

A dynamical trajectory-based methodology for systematically computing multiple optimal solutions of general nonlinear programming problems.
IEEE Trans. Autom. Control., 2004

An optimization-driven framework for the computation of the controlling UEP in transient stability analysis.
IEEE Trans. Autom. Control., 2004

Multi-stage Neural Networks for Channel Assignment in Cellular Radio Networks.
Proceedings of the Advances in Neural Networks, 2004

A Novel Three-Phase Algorithm for RBF Neural Network Center Selection.
Proceedings of the Advances in Neural Networks, 2004

A Regularized Line Search Tunneling for Efficient Neural Network Learning.
Proceedings of the Advances in Neural Networks, 2004

Efficient Option Pricing via a Globally Regularized Neural Network.
Proceedings of the Advances in Neural Networks, 2004

2003
Dynamic gradient approaches to compute the closest unstable equilibrium point for stability region estimate and their computational limitations.
IEEE Trans. Autom. Control., 2003

A novel homotopy-based algorithm for the closest unstable equilibrium point method in nonlinear stability analysis.
Proceedings of the 2003 International Symposium on Circuits and Systems, 2003

2001
Quotient gradient methods for solving constraint satisfaction problems.
Proceedings of the 2001 International Symposium on Circuits and Systems, 2001

Computation of multiple type-one equilibrium points on the stability boundary using generalized fixed-point homotopy methods.
Proceedings of the 2001 International Symposium on Circuits and Systems, 2001

A trajectory-based methodology for systematically computing multiple optimal solutions of general nonlinear programming problems.
Proceedings of the 2001 International Symposium on Circuits and Systems, 2001

2000
Convergent regions of Newton homotopy methods for nonlinear systems: theory and computational applications.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2000

Stability regions of non-hyperbolic dynamical systems: theory and optimal estimation.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2000


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