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cs.LG2026
Robust Bayesian Optimization with Q-Exponential Surrogates
Richard Cornelius Suwandi, Zhidi Lin, Feng Yin +1
Bayesian optimization (BO) is a widely used framework for optimizing expensive black-box objectives, but standard BO methods often use Gaussian process (GP) surrogates whose Gaussi…
cs.LG2024
Regularization-Based Efficient Continual Learning in Deep State-Space Models
Yuanhang Zhang, Zhidi Lin, Yiyong Sun +2
Deep state-space models (DSSMs) have gained popularity in recent years due to their potent modeling capacity for dynamic systems. However, existing DSSM works are limited to single…
cs.LG2023★ 1 cited
Ensemble Kalman Filtering Meets Gaussian Process SSM for Non-Mean-Field and Online Inference
Zhidi Lin, Yiyong Sun, Feng Yin +1
The Gaussian process state-space models (GPSSMs) represent a versatile class of data-driven nonlinear dynamical system models. However, the presence of numerous latent variables in…