3 papers
stat.ML2020
Adaptive Covariate Acquisition for Minimizing Total Cost of Classification
Daniel Andrade, Yuzuru Okajima
In some applications, acquiring covariates comes at a cost which is not negligible. For example in the medical domain, in order to classify whether a patient has diabetes or not, m…
stat.ME2019
Disjunct Support Spike and Slab Priors for Variable Selection in Regression under Quasi-sparseness
Daniel Andrade, Kenji Fukumizu
Sparseness of the regression coefficient vector is often a desirable property, since, among other benefits, sparseness improves interpretability. In practice, many true regression…
cs.AI2012
Lower Bound Bayesian Networks - An Efficient Inference of Lower Bounds on Probability Distributions in Bayesian Networks
Daniel Andrade, Bernhard Sick
We present a new method to propagate lower bounds on conditional probability distributions in conventional Bayesian networks. Our method guarantees to provide outer approximations…