2 citations · 2 across the 5 of their papers we have counts for
5 papers
Geometry-Aware Bayesian Quantification via Compositional Data Analysis
Alejandro Moreo, Pablo González, Juan José del Coz
Accurately estimating the unknown target label distribution is the critical first step for adapting to label shift. This task, widely known as quantification or class prevalence es…
Quantification via Gaussian Latent Space Representations
Olaya Pérez-Mon, Juan José del Coz, Pablo González
Quantification, or prevalence estimation, is the task of predicting the prevalence of each class within an unknown bag of examples. Most existing quantification methods in the lite…
Quantification using Permutation-Invariant Networks based on Histograms
Olaya Pérez-Mon, Alejandro Moreo, Juan José del Coz +1
Quantification, also known as class prevalence estimation, is the supervised learning task in which a model is trained to predict the prevalence of each class in a given bag of exa…
Kernel Density Estimation for Multiclass Quantification
Alejandro Moreo, Pablo González, Juan José del Coz
Several disciplines, like the social sciences, epidemiology, sentiment analysis, or market research, are interested in knowing the distribution of the classes in a population rathe…
Binary Quantification and Dataset Shift: An Experimental Investigation
Pablo González, Alejandro Moreo, Fabrizio Sebastiani
Quantification is the supervised learning task that consists of training predictors of the class prevalence values of sets of unlabelled data, and is of special interest when the l…