Sequence Analysis and Modeling Lab
This is a joint work by Behnam Gholami, Pritish Sahu, Minyoung Kim, Vladimir Pavlovic
Our new paper on Domain Adaptation was accepted in Multi-Discipline Approach for Learning Concepts – Zero-Shot, One-Shot, Few-Shot, and Beyond and Beyond Workshop in conjunction with ICCV 2019.
This is a joint work by Behnam Gholami, Pritish Sahu, Ognjen Rudovic, Konstantinos Bousmalis, Vladimir Pavlovic
Unsupervised domain adaptation (uDA) models focus on pairwise adaptation settings where there is a single, labeled, source and a single target domain. However, in many real-world settings … Read the rest
This is a joint work by Minyoung Kim, Pritish Sahu, Behnam Gholami, Vladimir Pavlovic.
For unsupervised domain adaptation, the target domain error can be provably reduced by having a shared input representation that makes the source and target domains … Read the rest