4 papers
Noise-Augmented Privacy-Preserving Empirical Risk Minimization with Dual-purpose Regularizer and Privacy Budget Retrieval and Recycling
Yinan Li, Fang Liu
We propose Noise-Augmented Privacy-Preserving Empirical Risk Minimization (NAPP-ERM) that solves ERM with differential privacy guarantees. Existing privacy-preserving ERM approache…
Continuous-time Markov-switching GARCH Process with Robust and Efficient State Path and Volatility Estimation
Yinan Li, Fang Liu
We propose a continuous-time Markov-switching generalized autoregressive conditional heteroskedasticity (COMS-GARCH) process for handling irregularly spaced time series (TS) with m…
AdaPtive Noisy Data Augmentation (PANDA) for Simultaneous Construction of Multiple Graph Models
Yinan Li, Xiao Liu, Fang Liu
We extend the data augmentation technique PANDA by Li et al. (2018) that regularizes single graph estimation to jointly learning multiple graphical models with various node types i…
PANDA: AdaPtive Noisy Data Augmentation for Regularization of Undirected Graphical Models
Yinan Li, Xiao Liu, Fang Liu
We propose an AdaPtive Noise Augmentation (PANDA) technique to regularize the estimation and construction of undirected graphical models. PANDA iteratively optimizes the objective…