3 citations · 3 across the 4 of their papers we have counts for
4 papers
Fast and Accurate Graph Learning for Huge Data via Minipatch Ensembles
Tianyi Yao, Minjie Wang, Genevera I. Allen
Gaussian graphical models provide a powerful framework for uncovering conditional dependence relationships between sets of nodes; they have found applications in a wide variety of…
Feature Selection for Huge Data via Minipatch Learning
Tianyi Yao, Genevera I. Allen
Feature selection often leads to increased model interpretability, faster computation, and improved model performance by discarding irrelevant or redundant features. While feature…
Supervised Convex Clustering
Minjie Wang, Tianyi Yao, Genevera I. Allen
Clustering has long been a popular unsupervised learning approach to identify groups of similar objects and discover patterns from unlabeled data in many applications. Yet, coming…
Clustered Gaussian Graphical Model via Symmetric Convex Clustering
Tianyi Yao, Genevera I. Allen
Knowledge of functional groupings of neurons can shed light on structures of neural circuits and is valuable in many types of neuroimaging studies. However, accurately determining…