1.9k citations · 3.7k across the 35 of their papers we have counts for
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Feature-Level Domain Adaptation
Wouter M. Kouw, Jesse H. Krijthe, Marco Loog +1
Domain adaptation is the supervised learning setting in which the training and test data are sampled from different distributions: training data is sampled from a source domain, wh…
Approximated and User Steerable tSNE for Progressive Visual Analytics
Nicola Pezzotti, Boudewijn P. F. Lelieveldt, Laurens van der Maaten +3
Progressive Visual Analytics aims at improving the interactivity in existing analytics techniques by means of visualization as well as interaction with intermediate results. One ke…
Learning Visual Features from Large Weakly Supervised Data
Armand Joulin, Laurens van der Maaten, Allan Jabri +1
Convolutional networks trained on large supervised dataset produce visual features which form the basis for the state-of-the-art in many computer-vision problems. Further improveme…