“Unsupervised Domain Adaptation with Copula Models” presented at MLSP’17

Our paper “Unsupervised Domain Adaptation with Copula Models”[1] was presented this week at the IEEE Int’l Workshop on Machine Learning for Signal Processing in Tokyo, Japan.

It was an exciting meeting; unlike the now mega-conferences of CVPR and NIPS kind, MLSP is still refreshingly small.  There were several outstanding tutorials and keynotes by Kenji Fukumizu, Shun-ichi Amari, and Yee Whye Teh, with limited emphasis on “deep.”  Well organized!

Then, there was Tokyo itself.  Always a pleasure to visit.


[1] [doi] C. D. Tran, O. Rudovic, and V. Pavlovic, “Unsupervised domain adaptation with copula models,” in IEEE Int’l Conf. Machine Learning for Signal Processing (MLSP), 2017.
author = {Cuong D. Tran and Ognjen Rudovic and Vladimir Pavlovic},
booktitle = {IEEE Int'l Conf. Machine Learning for Signal Processing (MLSP)},
title = {Unsupervised domain adaptation with copula models},
year = {2017},
note = {33\% contribution.},
date-added = {2017-01-17 15:43:46 +0000},
date-modified = {2017-01-17 15:45:08 +0000},
doi = {10.1109/mlsp.2017.8168131},
keywords = {domain adaptation, mlsp17},

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