4 papers
Provable Accelerated Bayesian Optimization with Knowledge Transfer
Haitao Lin, Boxin Zhao, Mladen Kolar +1
We study how to accelerate Bayesian optimization (BO) on a target task by transferring historical knowledge from related source tasks. Existing work on BO with knowledge transfer e…
SMART: A Spectral Transfer Approach to Multi-Task Learning
Boxin Zhao, Mladen Kolar, Jinchi Lv
Multi-task learning is effective for related applications, but its performance can deteriorate when the target sample size is small. Transfer learning can borrow strength from rela…
Trans-Glasso: A Transfer Learning Approach to Precision Matrix Estimation
Boxin Zhao, Cong Ma, Mladen Kolar
Precision matrix estimation is essential in various fields; yet it is challenging when samples for the target study are limited. Transfer learning can enhance estimation accuracy b…
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
Boxin Zhao, Lingxiao Wang, Ziqi Liu +4
Due to the high cost of communication, federated learning (FL) systems need to sample a subset of clients that are involved in each round of training. As a result, client sampling…