Dataset Groups Activity Stream Divergent-GAN for Positive Unlabeled learning The proposed approach incorporates a biased PU risk into a generic GAN framework to guide the generator convergence towards the negative samples distribution. BibTex: @dataset{Florent_Chiaroni_and_Ghazaleh_Khodabandeloub_and_Mohamed-Cherif_Rahala_and_Nicolas_Hueber_and_Frederic_Dufaux_2024, abstract = {The proposed approach incorporates a biased PU risk into a generic GAN framework to guide the generator convergence towards the negative samples distribution.}, author = {Florent Chiaroni and Ghazaleh Khodabandeloub and Mohamed-Cherif Rahala and Nicolas Hueber and Frederic Dufaux}, doi = {10.57702/9we8baye}, institution = {No Organization}, keyword = {'GAN-based PU framework', 'counter-examples generation', 'discriminator regularizations'}, month = {dec}, publisher = {TIB}, title = {Divergent-GAN for Positive Unlabeled learning}, url = {https://service.tib.eu/ldmservice/dataset/divergent-gan-for-positive-unlabeled-learning}, year = {2024} }
