EE ZOOM Seminar: Task Nuisance Filtration for Unsupervised Domain Adaptation
https://tau-ac-il.zoom.us/j/82634921282?pwd=7Im8wd0FCJ7D0pIAMVoNglffXBaUrY.1
Meeting ID: 826 3492 1282
Passcode: 115437
Electrical Engineering Systems ZOOM Seminar
Speaker: David Uliel
M.Sc. student under the supervision of Prof. Raja Giryes
Sunday, 22nd June 2025, at 15:00
Task Nuisance Filtration for Unsupervised Domain Adaptation
Abstract
In unsupervised domain adaptation (UDA) labeled data is available for one domain (Source
Domain) which is generated according to some distribution, and unlabeled data is available for a second domain (Target Domain) which is generated from a possibly different distribution but has the same task.
The goal is to learn a model that performs well on the target domain although labels are available only for the source data. Many recent works attempt to align the source and the target domains by matching their marginal distributions in a learned feature space. In this paper, we address the domain difference as a nuisance, and enables better adaptability of the domains, by encouraging minimality of the target domain representation, disentanglement of the features, and a smoother feature space that cluster better the target data. To this end, we use the information bottleneck theory and a classical technique from the blind source separation framework, namely, ICA (independent components analysis). We show that these concepts can
improve performance of leading domain adaptation methods on various domain adaptation benchmarks.
השתתפות בסמינר תיתן קרדיט שמיעה = עפ"י רישום בצ'ט של שם מלא + מספר ת.ז.
