19 citations · 64 across the 31 of their papers we have counts for
Showing 2016 · stat.MLShow all
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stat.ML2016
Kernel Alignment for Unsupervised Transfer Learning
Ievgen Redko, Younès Bennani
The ability of a human being to extrapolate previously gained knowledge to other domains inspired a new family of methods in machine learning called transfer learning. Transfer lea…
stat.ML2016
Theoretical Analysis of Domain Adaptation with Optimal Transport
Ievgen Redko, Amaury Habrard, Marc Sebban
Domain adaptation (DA) is an important and emerging field of machine learning that tackles the problem occurring when the distributions of training (source domain) and test (target…