@inbook{a712d918418741189bc977d527e44f25,
title = "Heterogeneous Domain Adaptation Based on Class Decomposition Schemes",
abstract = "This paper introduces a novel classification algorithm for heterogeneous domain adaptation. The algorithm projects both the target and source data into a common feature space of the class decomposition scheme used. The distinctive features of the algorithm are: (1) it does not impose any assumptions on the data other than sharing the same class labels; (2) it allows adaptation of multiple source domains at once; and (3) it can help improving the topology of the projected data for class separability. The algorithm provides two built-in classification rules and allows applying any other classification model.",
author = "Firat Ismailoglu and Evgueni Smirnov and Ralf Peeters and Shuang Zhou and Pieter Collins",
year = "2018",
month = jun,
day = "19",
doi = "10.1007/978-3-319-93034-3_14",
language = "English",
isbn = "978-3-319-93033-6",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "169--182",
editor = "D. Phung and V. Tseng and G. Webb and B. Ho and M. Ganji and L. Rashidi",
booktitle = "Advances in Knowledge Discovery and Data Mining",
address = "United States",
}