94 citations · 148 across the 10 of their papers we have counts for
5 papers · 1 filter
Incentives in Private Collaborative Machine Learning
Rachael Hwee Ling Sim, Yehong Zhang, Trong Nghia Hoang +3
Collaborative machine learning involves training models on data from multiple parties but must incentivize their participation. Existing data valuation methods fairly value and rew…
Model Provenance via Model DNA
Xin Mu, Yu Wang, Yehong Zhang +4
Understanding the life cycle of the machine learning (ML) model is an intriguing area of research (e.g., understanding where the model comes from, how it is trained, and how it is…
Dependency Structure Search Bayesian Optimization for Decision Making Models
Mohit Rajpal, Lac Gia Tran, Yehong Zhang +1
Many approaches for optimizing decision making models rely on gradient based methods requiring informative feedback from the environment. However, in the case where such feedback i…
Collaborative Machine Learning with Incentive-Aware Model Rewards
Rachael Hwee Ling Sim, Yehong Zhang, Mun Choon Chan +1
Collaborative machine learning (ML) is an appealing paradigm to build high-quality ML models by training on the aggregated data from many parties. However, these parties are only w…
Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression
Tong Teng, Jie Chen, Yehong Zhang +1
This paper presents a variational Bayesian kernel selection (VBKS) algorithm for sparse Gaussian process regression (SGPR) models. In contrast to existing GP kernel selection algor…