<--- Back to Details
First PageDocument Content
Stochastic optimization / Probability theory / Stochastic approximation / Mathematical optimization / Bayesian inference / Latent Dirichlet allocation / Expectation–maximization algorithm / Variational Bayesian methods / Statistics / Bayesian statistics / Estimation theory
Date: 2015-03-12 00:16:22
Stochastic optimization
Probability theory
Stochastic approximation
Mathematical optimization
Bayesian inference
Latent Dirichlet allocation
Expectation–maximization algorithm
Variational Bayesian methods
Statistics
Bayesian statistics
Estimation theory

An Adaptive Learning Rate for Stochastic Variational Inference Rajesh Ranganath Princeton University, 35 Olden St., Princeton, NJ[removed]RAJESHR @ CS . PRINCETON . EDU

Add to Reading List

Source URL: www.cs.columbia.edu

Download Document from Source Website

File Size: 1,01 MB

Share Document on Facebook

Similar Documents

Cataloging the Visible Universe through Bayesian Inference at Petascale Jeffrey Regier∗ , Kiran Pamnany† , Keno Fischer‡ , Andreas Noack§ , Maximilian Lam∗ , Jarrett Revels§ , Steve Howard¶ , Ryan Giordano¶ ,

Cataloging the Visible Universe through Bayesian Inference at Petascale Jeffrey Regier∗ , Kiran Pamnany† , Keno Fischer‡ , Andreas Noack§ , Maximilian Lam∗ , Jarrett Revels§ , Steve Howard¶ , Ryan Giordano¶ ,

DocID: 1xVn9 - View Document

Haptic SLAM: an ideal observer model for Bayesian inference of object shape and hand pose from contact dynamics Feryal M. P. Behbahani1 , Guillem Singla–Buxarrais2 and A. Aldo Faisal1,2,3 1

Haptic SLAM: an ideal observer model for Bayesian inference of object shape and hand pose from contact dynamics Feryal M. P. Behbahani1 , Guillem Singla–Buxarrais2 and A. Aldo Faisal1,2,3 1

DocID: 1xTqR - View Document

Improving the Identifiability of Neural Networks for Bayesian Inference Arya A. Pourzanjani∗, Richard M. Jiang∗, Linda R. Petzold Department of Computer Science University of California, Santa Barbara

Improving the Identifiability of Neural Networks for Bayesian Inference Arya A. Pourzanjani∗, Richard M. Jiang∗, Linda R. Petzold Department of Computer Science University of California, Santa Barbara

DocID: 1uZys - View Document

MAP estimate on GLMs  Stochastic Gradient Descent (SGD) MAP to Bayesian Inference

MAP estimate on GLMs Stochastic Gradient Descent (SGD) MAP to Bayesian Inference

DocID: 1uTAz - View Document

Bayesian Analysis, Number 4, pp. 817–846 Inference of global clusters from locally distributed data

Bayesian Analysis, Number 4, pp. 817–846 Inference of global clusters from locally distributed data

DocID: 1uGu0 - View Document