Title
Partial Domain Adaptation Using Selective Representation Learning For Class-Weight Computation
Abstract
The generalization power of deep-learning models is dependent on rich-labelled data. This supervision using large-scaled annotated information is restrictive in most realworld scenarios where data collection and their annotation involve huge cost. Various domain adaptation techniques exist in literature that bridge this distribution discrepancy. However, a majority of these models require the labe...
Year
DOI
Venue
2020
10.1109/IEEECONF51394.2020.9443420
2020 54th Asilomar Conference on Signals, Systems, and Computers
Keywords
DocType
ISBN
Computers,Bridges,Adaptation models,Annotations,Computational modeling,Data collection,Benchmark testing
Conference
978-0-7381-3126-9
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Sandipan Choudhuri100.34
Riti Paul200.34
Arunabha Sen3859118.33
Baoxin Li4101794.72
Hemanth Venkateswara5239.72