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Sequence Analysis and Modeling Lab

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Author: Pritish Sahu

Posted on September 22, 2019October 2, 2019

Task-Discriminative Domain Alignment for Unsupervised Domain Adaptation

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.

Abstract

… Read the rest
Posted on September 22, 2019October 2, 2019

Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach

This is a joint work by Behnam Gholami, Pritish Sahu, Ognjen Rudovic, Konstantinos Bousmalis, Vladimir Pavlovic

Abstract

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

Posted on July 9, 2019October 2, 2019

Unsupervised Visual Domain Adaptation:A Deep Max-Margin Gaussian Process Approach : Oral Paper at CVPR 2019

This is a joint work by Minyoung Kim, Pritish Sahu, Behnam Gholami, Vladimir Pavlovic.

Abstract

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

Recent Posts

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  • New NSF Grant: Learning Joint Crowd-Space Embeddings for Cross-Modal Crowd Behavior Prediction

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    SEQAM Lab
    CBIM Center
    Rutgers University
    617 Bowser Road
    Piscataway, New Jersey 08854
    United States of America
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