350 citations · 497 across the 6 of their papers we have counts for
4 papers · 1 filter
Beta Process Non-negative Matrix Factorization with Stochastic Structured Mean-Field Variational Inference
Dawen Liang, Matthew D. Hoffman
Beta process is the standard nonparametric Bayesian prior for latent factor model. In this paper, we derive a structured mean-field variational inference algorithm for a beta proce…
Learning Activation Functions to Improve Deep Neural Networks
Forest Agostinelli, Matthew Hoffman, Peter Sadowski +1
Artificial neural networks typically have a fixed, non-linear activation function at each neuron. We have designed a novel form of piecewise linear activation function that is lear…
Image Classification and Retrieval from User-Supplied Tags
Hamid Izadinia, Ali Farhadi, Aaron Hertzmann +1
This paper proposes direct learning of image classification from user-supplied tags, without filtering. Each tag is supplied by the user who shared the image online. Enormous numbe…
Structured Stochastic Variational Inference
Matthew D. Hoffman, David M. Blei
Stochastic variational inference makes it possible to approximate posterior distributions induced by large datasets quickly using stochastic optimization. The algorithm relies on t…