82 citations · 926 across the 70 of their papers we have counts for
7 papers · 1 filter
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…
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…
ANODEV2: A Coupled Neural ODE Evolution Framework
Tianjun Zhang, Zhewei Yao, Amir Gholami +4
It has been observed that residual networks can be viewed as the explicit Euler discretization of an Ordinary Differential Equation (ODE). This observation motivated the introducti…
ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs
Amir Gholami, Kurt Keutzer, George Biros
Residual neural networks can be viewed as the forward Euler discretization of an Ordinary Differential Equation (ODE) with a unit time step. This has recently motivated researchers…
Far-Field Compression for Fast Kernel Summation Methods in High Dimensions
William B. March, George Biros
We consider fast kernel summations in high dimensions: given a large set of points in dimensions (with ) and a pair-potential function (the {\em kernel} function), we…