5 papers
Proximal-IMH: Proximal Posterior Proposals for Independent Metropolis-Hastings with Approximate Operators
Youguang Chen, George Biros
We consider the problem of sampling from a posterior distribution arising in Bayesian inverse problems in science, engineering, and imaging. Our method belongs to the family of ind…
Latent-IMH: Efficient Bayesian Inference for Inverse Problems with Approximate Operators
Youguang Chen, George Biros
We study sampling from posterior distributions in Bayesian linear inverse problems where , the parameters to observables operator, is computationally expensive. In many applicat…
Extensions of the regret-minimization algorithm for optimal design
Youguang Chen, George Biros
We consider the problem of selecting a subset of points from a dataset of unlabeled examples for labeling, with the goal of training a multiclass classifier. To address this, w…
A Scalable Algorithm for Active Learning
Youguang Chen, Zheyu Wen, George Biros
FIRAL is a recently proposed deterministic active learning algorithm for multiclass classification using logistic regression. It was shown to outperform the state-of-the-art in ter…
FIRAL: An Active Learning Algorithm for Multinomial Logistic Regression
Youguang Chen, George Biros
We investigate theory and algorithms for pool-based active learning for multiclass classification using multinomial logistic regression. Using finite sample analysis, we prove that…