2 citations · 5 across the 4 of their papers we have counts for
4 papers
Verifying the Selected Completely at Random Assumption in Positive-Unlabeled Learning
Paweł Teisseyre, Konrad Furmańczyk, Jan Mielniczuk
The goal of positive-unlabeled (PU) learning is to train a binary classifier on the basis of training data containing positive and unlabeled instances, where unlabeled observations…
A construction of a graphical model
Konrad Furmańczyk
We present a nonparametric graphical model. Our model uses an undirected graph that represents conditional independence for general random variables defined by the conditional depe…
Network Model with Application to Allergy Diseases
Konrad Furmańczyk, Wojciech Niemiro, Mariola Chrzanowska +1
We propose a new graphical model to describe the comorbidity of allergic diseases. We present our model in two versions. First, we introduce a generative model that correctly refle…
Double logistic regression approach to biased positive-unlabeled data
Konrad Furmańczyk, Jan Mielniczuk, Wojciech Rejchel +1
Positive and unlabelled learning is an important problem which arises naturally in many applications. The significant limitation of almost all existing methods lies in assuming tha…