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<!DOCTYPE html>
<html>
<head>
<link rel="stylesheet" href="style.css" />
<link rel="stylesheet" href="./Fonts/fa/css/all.css">
<link rel="stylesheet" href="./Fonts/ac/css/academicons.css">
<script type="text/javascript">
function show_bib(pubid){
var bibStatus = document.getElementById(pubid).style.display;
if (bibStatus === 'block') document.getElementById(pubid).style.display = 'none';
else document.getElementById(pubid).style.display = 'block';
}
</script>
<title>Nikos Kargas</title>
</head>
<body>
<div id="tlayout">
<div id="layout-content">
<div id="toptitle">
<h1><strong>Nikos Kargas</strong></h1>
</div>
<div id='info'>
<div class="imgtable">
<img src="Pics/pic.png" width=150 style="height: auto" alt="pic" />
</div>
<div id='contact'>
<p>
I am an Applied Scientist at Amazon Alexa AI, working on Natural Language Processing (NLP) techniques for improving
expressivity and flexibility of Text-to-Speech (TTS) systems.
</br>
</br>
I received my PhD degree in
<a href="http://www.ece.umn.edu/">Electrical and Computer Engineering</a> from the
<a href="http://twin-cities.umn.edu/">University of Minnesota</a> under the supervision of Professor
<a href="http://www.ece.virginia.edu/~nds5j">Nikolaos D. Sidiropoulos</a> in Dec. 2020. My PhD work leverages tensor decompositions
for developing efficient, robust and interpretable ML models. Applications include non-parametric density estimation,
missing data imputation, recommender systems, spatio-temporal data analysis and time-series forecasting.
</p>
<div id='links'>
<a href="https://gr.linkedin.com/in/nkargas"> <i class="fab fa-linkedin fa-2x"></i></a>
<a href="https://www.researchgate.net/profile/Nikos_Kargas"> <i class="fab fa-researchgate fa-2x"></i></a>
<a href="https://github.com/nkargas"> <i class="fab fa-github fa-2x"></i></a>
<a href="https://scholar.google.com/citations?user=Na3iAdMAAAAJ&hl=en"><i class="ai ai-google-scholar-square ai-2x"></i></a>
<br />
Email: karga005 at umn.edu
<br />
</div>
</div>
</div>
<h2><strong>News</strong></h2>
<ul>
<li>
<strong>05/2022</strong>: Our paper "Low-rank Characteristic Tensor Density Estimation Part I: Foundations" has been accepted at IEEE Transactions on Signal Processing.
</li>
<li>
<strong>03/2022</strong>: Our paper "Low-rank Characteristic Tensor Density Estimation Part II: Compression and Latent Density Estimation" has been accepted at IEEE Transactions on Signal Processing.
</li>
<li>
<strong>11/2021</strong>: Our paper "Information-Theoretic Feature Selection via Tensor Decomposition and Submodularity" has been accepted at IEEE Transactions on Signal Processing.
</li>
<li>
<strong>05/2021</strong>: Our paper "Multi-version Tensor Completion for Time-delayed Spatio-temporal Data" has been accepted at IJCAI 2021!
</li>
<li>
<strong>04/2021</strong>: I Joined Amazon TTS in Cambridge, United Kingdom as an Applied Scientist!
</li>
</ul>
<!-- <h2><strong>Projects</strong></h2>
<ul>
<li>
<strong>01/2021</strong>: <a href="./Notebooks/Spatio-temporal%20Tensor%20Factorization%20with%20Latent%20Epidemiological%20Regularization.html"> STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization</a>
</li>
</ul> -->
<h2><strong>Research</strong></h2>
<h3><strong>2022</strong></h3>
<div class='publication'>
<a href="https://ieeexplore.ieee.org/document/9779133"><b>Low-rank Characteristic Tensor Density Estimation Part I: Foundations</b></a>
<br />
M. Amiridi, <strong>N. Kargas</strong>, N. D. Sidiropoulos
<br />
<em>IEEE Transactions on Signal Processing, 2022</em>
<br />
<a href="https://arxiv.org/abs/2008.12315"><b>[arxiv]</b></a>
</div>
<div class='publication'>
<a href="https://ieeexplore.ieee.org/document/9740538"><b>Low-rank Characteristic Tensor Density Estimation Part II: Compression and latent density estimation</b></a>
<br />
M. Amiridi, <strong>N. Kargas</strong>, N. D. Sidiropoulos
<br />
<em>IEEE Transactions on Signal Processing, 2022</em>
<br />
<a href="https://arxiv.org/abs/2106.10591"><b>[arxiv]</b></a>
</div>
<h3><strong>2021</strong></h3>
<div class='publication'>
<a href="https://ieeexplore.ieee.org/document/9606533"><b>Information-Theoretic Feature Selection via Tensor Decomposition and Submodularity</b></a>
<br />
M. Amiridi, <strong>N. Kargas</strong>, N. D. Sidiropoulos
<br />
<em>IEEE Transactions on Signal Processing, 2021</em>
<br />
<a href="https://arxiv.org/abs/2010.16181"><b>[arxiv]</b></a>
<a href="index.html"><b>[slides]</b></a>
</div>
<div class='publication'>
<a href="https://www.ijcai.org/proceedings/2021/0400.pdf"><b>Multi-version Tensor Completion for Time-delayed Spatio-temporal Data</b></a>
<br />
C. Qian, <strong>N. Kargas</strong>, C. Xiao, L. M. Glass, N. D. Sidiropoulos, J. Sun
<br />
<em>International Joint Conference on Artificial Intelligence (IJCAI), 2021</em>
<br />
(acceptance rate = <strong>13.9%</strong>).
<br />
<a href="https://arxiv.org/abs/2105.05326"><b>[arxiv]</b></a>
<a href="index.html"><b>[slides]</b></a>
<a href="./Files/posters/IJCAI_2021.pdf"><b>[poster]</b></a>
<a href="javascript:show_bib('QianKar2021')"><b>[bib]</b></a>
<div class="bib-text" id="QianKar2021">
@inproceedings{QianKar2021,
title = {Multi-version Tensor Completion for Time-delayed Spatio-temporal Data},
author = {Qian, Cheng and Kargas, Nikos and Xiao, Cao and Glass, Lucas M. and Sidiropoulos, Nicholas D. and Sun, Jimeng},
booktitle = {Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, {IJCAI-21}},
pages = {2906--2912},
year = {2021}
}
</div>
</div>
<div class='publication'>
<a href="https://ojs.aaai.org/index.php/AAAI/article/view/16615"><b>STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization</b></a>
<br />
<strong>N. Kargas</strong>, C. Qian, N. D. Sidiropoulos, C. Xiao, L. M. Glass and J. Sun
<br />
<em>AAAI Conference on Artificial Intelligence (AAAI), 2021</em>
<br />
(acceptance rate = <strong>21%</strong>).
<br />
<a href="https://www.youtube.com/watch?v=NmAB4jljlxE"><b>Presentation</b></a> (Presented by Professor Jimeng Sun)
<br />
<a href="https://arxiv.org/abs/2012.04747"><b>[arxiv]</b></a>
<a href="./Files/presentations/AAAI_2021.pdf"><b>[slides]</b></a>
<a href="./Files/posters/AAAI_2021.pdf"><b>[poster]</b></a>
<a href="https://github.com/nkargas/STELAR"><b>[code]</b></a>
<a href="javascript:show_bib('KarQian2021')"><b>[bib]</b></a>
<div class="bib-text" id="KarQian2021">
@inproceedings{KarQian2021,
title = {{STELAR}: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization},
booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
author = {Kargas, Nikos and Qian, Cheng and Sidiropoulos, Nicholas D. and Xiao, Cao and Glass, Lucas M. and Sun, Jimeng},
year = {2021},
pages = {4830-4837}
}
</div>
</div>
<div class='publication'>
<a href="https://ieeexplore.ieee.org/abstract/document/9340610"><b>Supervised Learning and Canonical Decomposition of Multivariate Functions</b></a>
<br />
<strong>N. Kargas</strong> and N. D. Sidiropoulos
<br />
<em>IEEE Transactions on Signal Processing, 2021</em>
<br />
<a href="https://www.youtube.com/watch?v=epRT4izaWjk"><b>Presentation</b></a> (Presented by Professor N. D. Sidiropoulos)
<br />
<a href="javascript:show_bib('karSid2021')"><b>[bib]</b></a>
<div class="bib-text" id="karSid2021">
@article{karSid2021,
title = {Supervised learning and canonical decomposition of multivariate functions},
author = {Kargas, Nikos and Sidiropoulos, Nicholas D},
journal = {IEEE Transactions on Signal Processing},
volume = {69},
pages = {1097-1107},
year = {2021}
}
</div>
</div>
<h3><strong>2020</strong></h3>
<div class='publication'>
<a href="https://ieeexplore.ieee.org/document/9443399"><b>Supervised Learning via Ensemble Tensor Completion</b></a>
<br />
<strong>N. Kargas</strong> and N. D. Sidiropoulos
<br />
<em>Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2020</em>
<br />
<a href="./Files/videos/SupervisedLearningViaEnsembleTensorCompletion.mp4"><b>Presentation</b></a>
<br />
<a href="./Files/presentations/ASILOMAR_2020.pdf"><b>[slides]</b></a>
<a href="javascript:show_bib('KarSid2020b')"><b>[bib]</b></a>
<div class="bib-text" id="KarSid2020b">
@inproceedings{KarSid2020b,
author = {Kargas, Nikos and Sidiropoulos, Nicholas D.},
booktitle = {54th Asilomar Conference on Signals, Systems, and Computers},
title = {Supervised Learning via Ensemble Tensor Completion},
year = {2020},
pages = {196-199}
}
</div>
</div>
<div class='publication'>
<a href="https://aaai.org/ojs/index.php/AAAI/article/view/5868"><b>Nonlinear System Identification via Tensor Completion</b></a>
<br />
<strong>N. Kargas</strong> and N. D. Sidiropoulos
<br />
<em>AAAI Conference on Artificial Intelligence (AAAI), 2020 (<font color="red"><strong>Spotlight</strong></font>)</em>
<br />
(acceptance rate = <strong>20.6%</strong>).
<br />
<a href="https://www.youtube.com/watch?v=O5dgFVIOSBU"><b>Presentation</b></a> (Presented by Professor N. D. Sidiropoulos)
<br />
<a href="https://arxiv.org/abs/1906.05746"><b>[arxiv]</b></a>
<a href="./Files/presentations/AAAI_2020.pdf"><b>[slides]</b></a>
<a href="./Files/posters/AAAI_2020.pdf"><b>[poster]</b></a>
<a href="https://github.com/nkargas/Canonical-System-Identification"><b>[code]</b></a>
<a href="javascript:show_bib('KarSid2020a')"><b>[bib]</b></a>
<div class="bib-text" id="KarSid2020a">
@inproceedings{KarSid2020a,
title = {Nonlinear System Identification via Tensor Completion},
booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
author = {Kargas, Nikos and Sidiropoulos, Nicholas D.},
year = {2020},
pages = {4420-4427}
}
</div>
</div>
<h3><strong>2019</strong></h3>
<div class='publication'>
<a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7087548/"><b>Low-Rank Tensor Models for Improved Multi-Dimensional MRI: Application to Dynamic Cardiac T1 Mapping</b></a>
<br />
B. Yaman, S. Weingartner, <strong>N. Kargas</strong>, N. D. Sidiropoulos and M. Akcakaya
<br />
<em>IEEE Transactions on Computational Imaging, 2019</em>
<br />
<a href="javascript:show_bib('YamWein2020')"><b>[bib]</b></a>
<div class="bib-text" id="YamWein2020">
@article{YamWein2020,
author = {Yaman, Burhaneddin and Weingärtner, Sebastian and Kargas, Nikolaos and Sidiropoulos, Nicholas D. and Akçakaya, Mehmet},
journal = {IEEE Transactions on Computational Imaging},
title = {Low-Rank Tensor Models for Improved Multidimensional {MRI}: Application to Dynamic Cardiac {$T_1$} Mapping},
year = {2019},
volume = {6},
pages = {194-207}
}
</div>
</div>
<div class='publication'>
<a href="https://ieeexplore.ieee.org/document/8755580"><b>Statistical Learning Using Hierarchical Modeling of Probability Tensors</b></a>
<br />
M. Amiridi, <strong>N. Kargas</strong> and N. D. Sidiropoulos
<br />
<em>IEEE Data Science Workshop (DSW), 2019 (<font color="red"><strong>Best student paper award</strong></font>)</em>
<br />
<a href="./Files/presentations/DSW_2019.pdf"><b>[slides]</b></a>
<a href="javascript:show_bib('AmiKar2019')"><b>[bib]</b></a>
<div class="bib-text" id="AmiKar2019">
@inproceedings{AmiKar2019,
author = {Amiridi, Magda and Kargas, Nikos and Sidiropoulos, Nicholas D.},
booktitle = {2019 IEEE Data Science Workshop (DSW)},
title = {Statistical Learning Using Hierarchical Modeling of Probability Tensors},
year = {2019},
pages = {290-294}
}
</div>
</div>
<div class='publication'>
<a href="https://papers.nips.cc/paper/8999-crowdsourcing-via-pairwise-co-occurrences-identifiability-and-algorithms.pdf"><b>Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms</b></a>
<br />
S. Ibrahim, X. Fu, <strong>N. Kargas</strong> and K. Huang
<br />
<em>Advances in Neural Information Processing Systems (NeurIPS), 2019</em>
<br />
(acceptance rate = <strong>21%</strong>).
<br />
<a href="https://arxiv.org/abs/1909.12325"><b>[arxiv]</b></a>
<a href="./Files/presentations/NEURIPS_2019.pdf"><b>[slides]</b></a>
<a href="https://github.com/shahanaibrahimosu/crowdsourcing/tree/master/Code/Code"><b>[code]</b></a>
<a href="javascript:show_bib('IbrFu2019')"><b>[bib]</b></a>
<div class="bib-text" id="IbrFu2019">
@inproceedings{IbrFu2019,
title = {Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms},
author = {Ibrahim, Shahana and Fu, Xiao and Kargas, Nikolaos and Huang, Kejun},
booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
pages = {7847--7857},
volume = {32},
year = {2019}
}
</div>
</div>
<div class='publication'>
<a href="http://proceedings.mlr.press/v89/kargas19a/kargas19a.pdf"><b>Learning Mixtures of Smooth Product Distributions: Identifiability and Algorithm</b></a>
<br />
<strong>N. Kargas</strong> and N. D. Sidiropoulos
<br />
<em>International Conference on Artificial Intelligence and Statistics (AISTATS), 2019</em>
<br />
(acceptance rate = <strong>30%</strong>).
<br />
<a href="https://arxiv.org/abs/1904.01156"><b>[arxiv]</b></a>
<a href="./Files/posters/AISTATS_2019.pdf"><b>[poster]</b></a>
<a href="https://github.com/nkargas/Learning-mixtures-of-smooth-product-distributions"><b>[code]</b></a>
<a href="javascript:show_bib('KarSid2019')"><b>[bib]</b></a>
<div class="bib-text" id="KarSid2019">
@inproceedings{KarSid2019,
title = {Learning Mixtures of Smooth Product Distributions: Identifiability and Algorithm},
author = {Kargas, Nikos and Sidiropoulos, Nicholas D},
booktitle = {Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS)},
pages = {388--396},
year = {2019}
}
</div>
</div>
<h3><strong>2018</strong></h3>
<div class='publication'>
<a href="https://ieeexplore.ieee.org/document/8424892"><b>Tensors, Learning, and `Kolmogorov Extension' for Finite-alphabet Random Vectors</b></a>
<br />
<strong>N. Kargas</strong>, N. D. Sidiropoulos and X. Fu
<br />
<em>IEEE Transactions on Signal Processing, 2018</em>
<br />
<a href="https://arxiv.org/abs/1712.00205"><b>[arxiv]</b></a>
<a href="./Files/presentations/TSP_2018.pdf"><b>[slides]</b></a>
<a href="javascript:show_bib('KarSid2018')"><b>[bib]</b></a>
<div class="bib-text" id="KarSid2018">
@article{KarSid2018,
author = {N. {Kargas} and N. D. {Sidiropoulos} and X. {Fu}},
journal = {IEEE Transactions on Signal Processing},
title = {Tensors, Learning, and ``{Kolmogorov} Extension'' for Finite-Alphabet Random Vectors},
volume = {66},
number = {18},
pages = {4854--4868},
year = {2018}
}
</div>
</div>
<h3><strong>2017</strong></h3>
<div class='publication'>
<a href="https://ieeexplore.ieee.org/document/8313075"><b>Locally Low-Rank tensor regularization for high-resolution quantitative dynamic MRI</b></a>
<br />
B. Yaman, S. Weingartner, <strong> N. Kargas</strong>, N. D. Sidiropoulos and M. Akcakaya
<br />
<em>IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2017</em>
<br />
<a href="index.html"><b>[bib]</b></a>
</div>
<div class='publication'>
<a href="http://spars2017.lx.it.pt/index_files/papers/SPARS2017_Paper_110.pdf"><b>Low-Rank Tensor Regularization for Improved Dynamic Quantitative Magnetic Resonance Imaging</b></a>
<br />
<strong> N. Kargas</strong>, S. Weingartner, N. D. Sidiropoulos and M. Akcakaya
<br />
<em>Signal Processing with Adaptive Sparse Structured Representations Workshop (SPARS), 2017</em>
<br />
<a href="index.html"><b>[poster]</b></a>
<a href="index.html"><b>[bib]</b></a>
</div>
<div class='publication'>
<a href="https://ieeexplore.ieee.org/document/8023474"><b>Completing a Joint PMF from Projections: a Low-rank Coupled Tensor Factorization Approach</b></a>
<br />
<strong> N. Kargas</strong> and N. D. Sidiropoulos
<br />
<em>Information Theory and Applications Workshop (ITA), 2017</em>
<br />
<a href="https://arxiv.org/abs/1702.05184"><b>[arxiv]</b></a>
<a href="./Files/presentations/TSP_2018.pdf"><b>[slides]</b></a>
<a href="index.html"><b>[bib]</b></a>
</div>
<h3><strong>2015</strong></h3>
<div class='publication'>
<a href="https://ieeexplore.ieee.org/document/7236869"><b>Fully-Coherent Reader with Commodity SDR for Gen2 FM0 and Computational RFID</b></a>
<br />
<strong> N. Kargas</strong>, F. Mavromatis and A. Bletsas
<br />
<em>IEEE Wireless Communications Letters, 2015</em>
<br />
<a href="https://github.com/nkargas/Gen2-UHF-RFID-Reader"><b>[code]</b></a>
<a href="index.html"><b>[bib]</b></a>
</div>
<h3><strong>2014</strong></h3>
<div class='publication'>
<a href="https://ieeexplore.ieee.org/document/6934197"><b>Channel Coding for Increased Range Bistatic Backscatter Radio: Experimental Results</b></a>
<br />
P. N. Alevizos, N. Fasarakis-Hilliard, K. Tountas, N. Agadakos, <strong> N. Kargas</strong> and A. Bletsas
<br />
<em>IEEE RFID Technology and Applications Conference (RFID-TA), 2014</em>
<br />
<a href="index.html"><b>[bib]</b></a>
</div>
</div>
</div>
</body>
</html>