most citedSampling in Dirichlet Process Mixture Models for Clustering Streaming Data

3 citations · 3 across the 2 of their papers we have counts for

collaborators

3 papers

cs.LG2022

CPU- and GPU-based Distributed Sampling in Dirichlet Process Mixtures for Large-scale Analysis

Or Dinari, Raz Zamir, John W. Fisher +1

In the realm of unsupervised learning, Bayesian nonparametric mixture models, exemplified by the Dirichlet Process Mixture Model (DPMM), provide a principled approach for adapting…

cs.LG2022

Common Failure Modes of Subcluster-based Sampling in Dirichlet Process Gaussian Mixture Models -- and a Deep-learning Solution

Vlad Winter, Or Dinari, Oren Freifeld

The Dirichlet Process Gaussian Mixture Model (DPGMM) is often used to cluster data when the number of clusters is unknown. One main DPGMM inference paradigm relies on sampling. Her…

cs.LG2022★ 3 cited

Sampling in Dirichlet Process Mixture Models for Clustering Streaming Data

Or Dinari, Oren Freifeld

Practical tools for clustering streaming data must be fast enough to handle the arrival rate of the observations. Typically, they also must adapt on the fly to possible lack of sta…