53 citations · 113 across the 16 of their papers we have counts for
4 papers · 1 filter
Truncated Variational Sampling for "Black Box" Optimization of Generative Models
Jörg Lücke, Zhenwen Dai, Georgios Exarchakis
We investigate the optimization of two probabilistic generative models with binary latent variables using a novel variational EM approach. The approach distinguishes itself from pr…
Can clustering scale sublinearly with its clusters? A variational EM acceleration of GMMs and -means
Dennis Forster, Jörg Lücke
One iteration of standard -means (i.e., Lloyd's algorithm) or standard EM for Gaussian mixture models (GMMs) scales linearly with the number of clusters , data points , an…
-means as a variational EM approximation of Gaussian mixture models
Jörg Lücke, Dennis Forster
We show that -means (Lloyd's algorithm) is obtained as a special case when truncated variational EM approximations are applied to Gaussian Mixture Models (GMM) with isotropic Ga…
Truncated Variational EM for Semi-Supervised Neural Simpletrons
Dennis Forster, Jörg Lücke
Inference and learning for probabilistic generative networks is often very challenging and typically prevents scalability to as large networks as used for deep discriminative appro…