15 citations · 19 across the 4 of their papers we have counts for
4 papers
Multiple Adaptive Bayesian Linear Regression for Scalable Bayesian Optimization with Warm Start
Valerio Perrone, Rodolphe Jenatton, Matthias Seeger +1
Bayesian optimization (BO) is a model-based approach for gradient-free black-box function optimization. Typically, BO is powered by a Gaussian process (GP), whose algorithmic compl…
An interpretable latent variable model for attribute applicability in the Amazon catalogue
Tammo Rukat, Dustin Lange, Cédric Archambeau
Learning attribute applicability of products in the Amazon catalog (e.g., predicting that a shoe should have a value for size, but not for battery-type at scale is a challenge. The…
Online Inference for Relation Extraction with a Reduced Feature Set
Maxim Rabinovich, Cédric Archambeau
Access to web-scale corpora is gradually bringing robust automatic knowledge base creation and extension within reach. To exploit these large unannotated---and extremely difficult…
Plackett-Luce regression: A new Bayesian model for polychotomous data
Cedric Archambeau, Francois Caron
Multinomial logistic regression is one of the most popular models for modelling the effect of explanatory variables on a subject choice between a set of specified options. This mod…