Combining Stochastic Adaptive Cubic Regularization with Negative Curvature for Nonconvex Optimization. - Seonho Park; Seung-Hyun Jung; Panos M. Pardalos (J. Optim. Theory Appl., 2020)

Homography augumented momentum constrastive learning for SAR image retrieval. - Seonho Park; Maciej Rysz; Kathleen M. Dipple; Panos M. Pardalos (CoRR, 2021)

Learning Optimization Proxies for Large-Scale Security-Constrained Economic Dispatch. - Wenbo Chen 001; Seonho Park; Mathieu Tanneau; Pascal Van Hentenryck (CoRR, 2021)

Interpreting rate-distortion of variational autoencoder and using model uncertainty for anomaly detection. - Seonho Park; George Adosoglou; Panos M. Pardalos (Ann. Math. Artif. Intell., 2022)

Lazy Network: A Word Embedding-Based Temporal Financial Network to Avoid Economic Shocks in Asset Pricing Models. - George Adosoglou; Seonho Park; Gianfranco Lombardo; Stefano Cagnoni; Panos M. Pardalos (Complex., 2022)

Risk-Aware Control and Optimization for High-Renewable Power Grids. - Neil Barry; Minas Chatzos; Wenbo Chen 001; Dahye Han; Chaofan Huang; Roshan Joseph; Michael Klamkin; Seonho Park; Mathieu Tanneau; Pascal Van Hentenryck; Shangkun Wang; Hanyu Zhang; et al. (CoRR, 2022)

Confidence-Aware Graph Neural Networks for Learning Reliability Assessment Commitments. - Seonho Park; Wenbo Chen 001; Dahye Han; Mathieu Tanneau; Pascal Van Hentenryck (CoRR, 2022)

Self-Supervised Primal-Dual Learning for Constrained Optimization. - Seonho Park; Pascal Van Hentenryck (AAAI, 2023)

Compact Optimization Learning for AC Optimal Power Flow. - Seonho Park; Wenbo Chen 001; Terrence W. K. Mak; Pascal Van Hentenryck (CoRR, 2023)

Self-Supervised Learning for Large-Scale Preventive Security Constrained DC Optimal Power Flow. - Seonho Park; Pascal Van Hentenryck (CoRR, 2023)

Deep data density estimation through Donsker-Varadhan representation. - Seonho Park; Panos M. Pardalos (Ann. Math. Artif. Intell., 2025)