3 papers
cs.LG2019
Learning Fair Representations for Kernel Models
Zilong Tan, Samuel Yeom, Matt Fredrikson +1
Fair representations are a powerful tool for establishing criteria like statistical parity, proxy non-discrimination, and equality of opportunity in learned models. Existing techni…
stat.ML2018
Scalable Algorithms for Learning High-Dimensional Linear Mixed Models
Zilong Tan, Kimberly Roche, Xiang Zhou +1
Linear mixed models (LMMs) are used extensively to model dependecies of observations in linear regression and are used extensively in many application areas. Parameter estimation f…
stat.ML2018
Learning Integral Representations of Gaussian Processes
Zilong Tan, Sayan Mukherjee
We propose a representation of Gaussian processes (GPs) based on powers of the integral operator defined by a kernel function, we call these stochastic processes integral Gaussian…