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<!DOCTYPE html>
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<p>1st International Workshop on</p>
<h1 class="mb-4 pb-0"><span>M</span>achine <span>L</span>earning for <span>I</span>rregular <span>T</span>ime <span>S</span>eries (ML4ITS2021)</h1>
<p class="mb-4 pb-0">Co-located with Virtual <a href="https://2021.ecmlpkdd.org/">ECML PKDD 2021</a></p>
<p class="mb-4 pb-0">Submission <a href =" https://easychair.org/conferences/?conf=ml4its2021">HERE</a> </p>
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<h2>NBEATS - Time-series forecasting using feed-forward networks</h2>
<p>Boris Oreshkin</p>
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<img src="assets/img/speakers/boris.jpeg" alt="Boris Oreshkin" class="img-fluid">
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<p>The author will talk about N-BEATS neural network architecture and its applications to time-series forecasting. He will describe the architecture design, motivation and cover extensive empirical evidence demonstrating its effectiveness in various scenarios such as zero-shot transfer across datasets and small data learning for electricity load forecasting.</p>
<h2>About</h2>
<p>Boris Oreshkin is currently a research scientist at Unity Technologies working on developing machine learning tools for AI assisted character animation in games. He has 15 years of experience in academic and industrial R&D covering areas of machine learning, signal processing, time series analysis, medical image processing and data science. While being an applied research scientist at Element AI, Boris developed the N-BEATS neural network architecture for univariate time-series forecasting in collaboration with Dmitri Carpov, Nicolas Chapados and Yoshua Bengio. His research interests include learning with limited labels, weakly supervised learning, multi-modal information processing, feed-forward and attention based architectures, information processing on graphs and modelling kinematics with machine learning. </p>
<!--<p> Alippi is an IEEE Fellow, Member of the Administrative Committee of the IEEE Computational Intelligence Society, Board of Governors member of the International Neural Network Society, Board of Directors member of the European Neural Network Society, Past Vice-President education of the IEEE Computational Intelligence Society, past associate editor of the IEEE Transactions on Emerging topics in computational intelligence, the IEEE Computational Intelligence Magazine, the IEEE-Transactions on Instrumentation and Measurements, the IEEE-Transactions on Neural Networks.
In 2018 he received IEEE CIS Outstanding Computational Intelligence Magazine Award, the 2016 Gabor award from the International Neural Networks Society and the IEEE Computational Intelligence Society Outstanding Transactions on Neural Networks and Learning Systems Paper Award; in 2013 the IBM Faculty award; in 2004 the IEEE Instrumentation and Measurement Society Young Engineer Award. </p>
<p>Current research activity addresses adaptation and learning in non-stationary environments, graph learning and Intelligence for embedded, IoT and cyber-physical systems.</p>
<p>He holds 8 patents, has published one monograph book, 7 edited books and about 200 papers in international journals and conference proceedings.</p>-->
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