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Found 6 papers, 2 papers with code
Improved prediction of future user activity in online A/B testing
In online randomized experiments or A/B tests, accurate predictions of participant inclusion rates are of paramount importance.
A Nonparametric Bayes Approach to Online Activity Prediction
We derive closed-form expressions for the number of new users expected in a given period, and a simple Monte Carlo algorithm targeting the posterior distribution of the number of days needed to attain a desired number of users; the latter is important for experimental planning.
Frequency and cardinality recovery from sketched data: a novel approach bridging Bayesian and frequentist views
We study how to recover the frequency of a symbol in a large discrete data set, using only a compressed representation, or sketch, of those data obtained via random hashing.
Projected Statistical Methods for Distributional Data on the Real Line with the Wasserstein Metric
As a byproduct of our approach, we are also able to derive faster routines for previous work on PCA for distributions.
Spatially dependent mixture models via the Logistic Multivariate CAR prior
We consider the problem of spatially dependent areal data, where for each area independent observations are available, and propose to model the density of each area through a finite mixture of Gaussian distributions.
Methodology Applications
Feature Selection via Mutual Information: New Theoretical Insights
Mutual information has been successfully adopted in filter feature-selection methods to assess both the relevancy of a subset of features in predicting the target variable and the redundancy with respect to other variables.
