3k citations · 24.2k across the 299 of their papers we have counts for
6 papers · 2 filters
A Scalable Bootstrap for Massive Data
Ariel Kleiner, Ameet Talwalkar, Purnamrita Sarkar +1
The bootstrap provides a simple and powerful means of assessing the quality of estimators. However, in settings involving large datasets---which are increasingly prevalent---the co…
Joint Modeling of Multiple Related Time Series via the Beta Process
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan +1
We propose a Bayesian nonparametric approach to the problem of jointly modeling multiple related time series. Our approach is based on the discovery of a set of latent, shared dyna…
Combinatorial clustering and the beta negative binomial process
Tamara Broderick, Lester Mackey, John Paisley +1
We develop a Bayesian nonparametric approach to a general family of latent class problems in which individuals can belong simultaneously to multiple classes and where each class ca…
Beta processes, stick-breaking, and power laws
Tamara Broderick, Michael I. Jordan, Jim Pitman
The beta-Bernoulli process provides a Bayesian nonparametric prior for models involving collections of binary-valued features. A draw from the beta process yields an infinite colle…
Cluster Forests
Donghui Yan, Aiyou Chen, Michael I. Jordan
With inspiration from Random Forests (RF) in the context of classification, a new clustering ensemble method---Cluster Forests (CF) is proposed. Geometrically, CF randomly probes a…
Multiway Spectral Clustering: A Margin-Based Perspective
Zhihua Zhang, Michael I. Jordan
Spectral clustering is a broad class of clustering procedures in which an intractable combinatorial optimization formulation of clustering is "relaxed" into a tractable eigenvector…