3 citations · 5 across the 4 of their papers we have counts for
4 papers
On the Utility Recovery Incapability of Neural Net-based Differential Private Tabular Training Data Synthesizer under Privacy Deregulation
Yucong Liu, Chi-Hua Wang, Guang Cheng
Devising procedures for auditing generative model privacy-utility tradeoff is an important yet unresolved problem in practice. Existing works concentrates on investigating the priv…
LU decomposition and Toeplitz decomposition of a neural network
Yucong Liu, Simiao Jiao, Lek-Heng Lim
It is well-known that any matrix has an LU decomposition. Less well-known is the fact that it has a 'Toeplitz decomposition' where 's are Toeplitz…
Path-following methods for Maximum a Posteriori estimators in Bayesian hierarchical models: How estimates depend on hyperparameters
Zilai Si, Yucong Liu, Alexander Strang
Maximum a posteriori (MAP) estimation, like all Bayesian methods, depends on prior assumptions. These assumptions are often chosen to promote specific features in the recovered est…
Regularizing Deep Neural Networks with Stochastic Estimators of Hessian Trace
Yucong Liu, Shixing Yu, Tong Lin
In this paper, we develop a novel regularization method for deep neural networks by penalizing the trace of Hessian. This regularizer is motivated by a recent guarantee bound of th…