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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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<br>
<h2>Call for papers</h2>
<!--<p>Here are some of our speakers</p>-->
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<div class="row">
<p>
<b>Time series</b> data are ubiquitous. The broad diffusion and adoption of <b>Internet of Things (IoT)</b> and major advances in <b>sensor technology</b> are examples of why such data have become <b>pervasive</b>. These technologies have applications in several domains, such as healthcare, finance, meteorology, and transportation. <b>Deep Neural Networks (DNNs)</b> have recently been used to create models that improve on the state of the art for some of these tasks. </p>
<p>Time series data influences both political and industrial decisions every day, yet there is, surprisingly, limited research in Machine Learning (ML) for time series - especially in situations where data is <b>scarce</b> or of <b>low quality</b>. In many <b>real-world applications</b>, we have the following two scenarios: 1) the amount of available training data is <b>limited</b>, or 2) there is a huge amount of available data which is <b>scarcely or not labeled</b> due to high costs of data collection and annotation. As a result, the future of Artificial Intelligence (AI) will be about <b>“doing more with less”</b>. We believe there is a need for focusing on modern AI techniques that can extract value from such challenging situations. These considerations can also contribute to the increasing need to address sustainability and privacy aspects of ML and AI. In this context, <b>heterogeneity</b> of the data (e.g. non-stationarity, multi-resolution, irregular sampling) as well as <b>noise</b>, pose further challenges. </p>
<p>
The main scope of this workshop is to advance the state-of-the-art in time series analysis for <b>“irregular”</b> time series. Here, we define time series to be “irregular” if they fall under one or several of the following categories:
<ul id="list">
<li> <b>Short</b>: univariate and multivariate time series with a limited amount of data and history,</li>
<li> <b>Multiresolution</b>: multivariate time series where each signal has a different granularity or resolution in terms of sampling frequency,</li>
<li> <b>Noisy</b>: univariate/multivariate time series with some additional perturbation appearing in different forms. In this class, we also include time series with missing data,</li>
<li> <b>Heterogeneous</b>: multivariate time series, usually collected by many physical systems, that exhibit different types of embedded, statistical patterns and behaviours,</li>
<li> <b>Scarcely labeled</b> and <b>unlabeled</b>: univariate/multivariate time series where only a small part of the data is labeled or completely unlabeled.</li>
</ul>
</p>
<p>
This workshop intends to offer the ideal context for dissemination and cross-pollination of novel ideas in designing machine learning models suitable to deal with irregular time series. We specifically call for contributions addressing one (or more) of the irregularity aspects mentioned above. Accordingly, topics of interest for the workshop include, but are not limited to:
<ul id="list">
<li>Methods for data imputation and Denoising,</li>
<li>Generative models for synthetic data generation</li>
<li>Transfer learning and transformer architectures for time series forecasting and classification,</li>
<li>Attention mechanisms for time series forecasting</li>
<li>Graph neural networks for anomaly detection and failure prediction,</li>
<li>Quantification of uncertainty,</li>
<li>Neural network architectures for time series classification and forecasting,</li>
<li>Unsupervised and self-supervised learning for different time Series related tasks,</li>
<li>Representation learning for time series,</li>
<li>Few-shot learning and time series classification in a low-data regime,</li>
<li>GANs for time series analysis (i.e. anomaly detection, data imputation, data augmentation, data generation, privacy),</li>
<li>Physical-informed deep neural networks for time series modeling,</li>
<li>(Deep) reservoir computing and spiking neural networks for time series and structured data analysis.</li>
</ul>
</p>
</div>
</div>
</section><!-- End About Section -->
<!-- ======= Organization Section ======= -->
<section id="organization">
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<div class="section-header">
<br>
<h2>Organization</h2>
<!--<p>Here are some of our speakers</p>-->
</div>
<h3>Program Chairs</h3>
<p>
<ul id="list">
<li> Massimiliano Ruocco (SINTEF Digital / Norwegian University of Science and Technology)</li>
<li> Erlend Aune (BI / Norwegian University of Science and Technology)</li>
<li> Claudio Gallicchio (Univeristy of Pisa)</li>
</ul>
</p>
<h3>Program Committee</h3>
<p>
<ul id="list">
<li>Sara Malacarne (Telenor Research)</li>
<li>Pierluigi Salvo Rossi (Norwegian University of Science and Technology)</li>
<li>Bjorn Magnus Mathisen (Sintef DIGITAL) </li>
<li>Per Gunnar Auran (Sintef DIGITAL)</li>
<li>Jo Eidsvik (Norwegian University of Science and Technology)</li>
<li>Leif Anders Thorsrud (BI)</li>
<li>Gard Spreeman (Telenor Research)</li>
<li>Pablo Ortiz (Telenor Research)</li>
<li>Vegard Larsen (BI / Norges Bank)</li>
<li>Stefano Nichele (Oslomet / Simula)</li>
<li>Filippo Maria Bianchi (UiT the Arctic University of Norway)</li>
<li>Juan-Pablo Ortega (St. Gallen University, Switzerland)</li>
<li>Azarakhsh Jalalvand (Ghent University-imec, Belgium and Princeton University, USA)</li>
<li>Benjamin Paaßen (Institute for Informatics, Humboldt-University of Berlin, Germany)</li>
<li>Petia Koprinkova-Hristova (Institute of Information and Communication Technologies, Bulgarian Academy of Sciences)</li>
</ul>
</p>
</div>
</section><!-- End Organization Section -->
<section id="submission">
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<div class="section-header">
<br>
<h2>Submission</h2>
<!--<p>Here are some of our speakers</p>-->
</div>
<div class="row">
<p>
Papers must be written in English and formatted according to the Springer <a href ="https://www.springer.com/gp/computer-science/lncs/new-latex-templates-available/15634678">LNCS guidelines</a> followed by the main conference. Regular and short papers presenting work completed or in progress are invited. <b>Regular papers</b> are expected to provide original and innovative contributions, should not exceed 16 pages including references. <b>Short papers</b>, describing innovative ongoing research showing relevant preliminary results, are maximum 6 pages. Papers must be submitted in PDF format online via an <a href =" https://easychair.org/conferences/?conf=ml4its2021">Easychair submission interface</a>.
</p>
<p>
Each submission will be evaluated on the basis of <b>relevance, significance of contribution and quality</b> by at least three members of the program committee. Submitted papers cannot be identical, or substantially similar to versions that are currently under review at another conference, have been previously published, or have been accepted for publication. All accepted papers will be published at ceur-ws.org (indexed by e.g. google scholar) or within Springer LNCS proceedings depending on the number of submissions. Reviews are <b>single-blind</b>. At least one author of each accepted paper is required to attend the workshop to present.
</p>
<p>
The workshop’s schedule is tailored to an online event format. As such, we plan to integrate live sessions by video conferencing, pre-recorded videos and discussions through a communication platform such as Slack. The workshop will include 3 Invited Talks in video conferencing (30 minutes + 15 minutes Q&A). Authors of accepted “paper contributions” (both oral and posters) will be asked to send a 10 minute video to be made available through the communication platform. During Poster Sessions, attendees will be encouraged to initiate discussions around the presented contributions in dedicated communication platform channels, possibly engaging one-to-one meetings. Papers selected as contributed talks will be presented by a 15-minutes live video (available also offline) followed by a 5 minutes live Q&A (by video conferencing).
</p>
<p>
To further encourage the exchange of ideas and discussions, the workshop will conclude with a <b>panel discussion</b> including invited speakers and program committee members. We will collect questions via an online form from the audience. Lunch and coffee breaks will be coordinated with the official schedule of the conference. During coffee breaks, the attendees will be encouraged to socialize and engage discussions through the communication platform.
</p>
</div>
</div>
</section><!-- End About Submission -->
<section id="dates">
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<div class="section-header">
<br>
<h2>Dates</h2>
<!--<p>Here some of the most important dates</p>-->
</div>
<div class="row">
<p>
<ul id="list">
<li>Paper Submission Deadline: <i><b>July 16, 2021 (Postponed)</b></i></li>
<li>Acceptance notification: <i><b>August 6, 2021 (Postponed)</b></i> </li>
<li>Camera ready deadline: <i><b>August 20, 2021 (Postponed)</b></i> </li>
<li>Workshop program and proceedings online: <i><b>September 1, 2021</b></i></li>
<li>Workshop Date: <i><b>September 13, 2021</b></i></li>
</ul>
</p>
</div>
</div>
</section><!-- End Speakers Section -->
<!-- ======= Speakers Section ======= -->
<section id="speakers">
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<div class="section-header">
<br>
<h2>Event Speakers</h2>
<p>Here are some of our speakers</p>
</div>
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<div class="col-lg-4 col-md-6">
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<img src="assets/img/speakers/alippi.jpeg" alt="Cesare Alippi" class="img-fluid">
<div class="details">
<h3><a href="https://alippi.faculty.polimi.it/">Cesare Alippi</a></h3>
<!--<h3><a href="alippi.html#speakers-details">Cesare Alippi</a></h3>-->
<p>Politecnico of Milano, Milano, Italy; Università della Svizzera italiana, Lugano, Switzerland</p>
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<a href="https://www.linkedin.com/in/cesare-alippi-52a5524/?originalSubdomain=it"><i class="bi bi-linkedin"></i></a>
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<img src="assets/img/speakers/spyros.jpeg" alt="Spyros Makridakis" class="img-fluid">
<div class="details">
<h3><a href="speaker-details.html">Spyros Makridakis</a></h3>
<p>Univ. of Nicosia, Institute For the Future (IFF) and the Makridakis Open Forecasting Center (MOFC)</p>
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<div class="col-lg-4 col-md-6">
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<img src="assets/img/speakers/boris.jpeg" alt="Boris Oreshkin" class="img-fluid">
<div class="details">
<h3><a href="boris.html">Boris Oreshkin</a></h3>
<p>Unity Technologies</p>
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<a href="https://twitter.com/boreshkin"><i class="bi bi-twitter"></i></a>
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</section><!-- End Speakers Section -->
<!-- ======= Schedule Section ======= -->
<section id="schedule" class="section-with-bg">
<div class="container" data-aos="fade-up">
<div class="section-header">
<h2>Event Schedule</h2>
<p>Here is our event schedule</p>
</div>
<!--<ul class="nav nav-tabs" role="tablist" data-aos="fade-up" data-aos-delay="100">
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<a class="nav-link" href="#afternoon" role="tab" data-bs-toggle="tab">Afternoon</a>
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<!--<h3 class="sub-heading">TBA</h3>-->
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<div class="row schedule-item">
<div class="col-md-2"><time>14:30</time></div>
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<h4>Introduction and opening remarks - <span>Massimiliano Ruocco</span></h4>
<!--<p>Fugit voluptas iusto maiores temporibus autem numquam magnam.</p>-->
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<div class="col-md-2"><time>14:45</time></div>
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<div class="speaker">
<img src="assets/img/speakers/alippi.jpeg" alt="Cesare Alippi">
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<h4><a href="alippi.html#speakers-details">Invited Talk - "Multivariate (graph) time-series imputation"</a> - <span>Cesare Alippi</span></h4>
<p></p>
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<div class="row schedule-item">
<div class="col-md-2"><time>15:30</time></div>
<div class="col-md-10">
<h4>Paper Presentation <span> Chair: Claudio Gallicchio</span></h4>
<p>- Homological Time Series Analysis of Sensor Signals from Power Plants - <span> Luciano Melodia and Richard Lenz</span></p>
<p>- Adversarial Generation of Temporal Data: A Critique on Fidelity of Synthetic Data - Ankur Debnath, Nitish Gupta, Govind Waghmare, Hardik Wadhwa, Siddhartha Asthana and Ankur Arora</p>
<p>- Continuous-Discrete Recurrent Kalman Networks for Irregular Time Series - Mona Schirmer, Mazin Eltayeb and Maja Rudolph</p>
</div>
</div>
<div class="row schedule-item">
<div class="col-md-2"><time>16:30</time></div>
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<h4>Coffee Break and Online Socialization</h4>
<!--<p>Fugit voluptas iusto maiores temporibus autem numquam magnam.</p>-->
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<div class="row schedule-item">
<div class="col-md-2"><time>16:45</time></div>
<div class="col-md-10">
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<img src="assets/img/speakers/boris.jpeg" alt="Boris Oreshkin">
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<h4><a href="boris.html#speakers-details">Invited Talk - "NBEATS - Time-series forecasting using feed-forward networks"</a> - <span>Boris Oreshkin</span></h4>
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<div class="col-md-2"><time>17:30</time></div>
<div class="col-md-10">
<h4>Panel and concluding remarks - <span>Erlend Aune</span></h4>
<p>- Sara Malacarne - Research Scientist, Telenor Research, Norway</p>
<p>- Juan-Pablo Ortega - Research Scientist, St. Gallen University, Switzerland</p>
<p>- Are Haartveit - Intelecy, Norway</p>
<p>- Filippo Maria Bianchi - University of Tromsø, Norway</p>
</div>
</div>
<div class="row schedule-item">
<div class="col-md-2"><time>18:00</time></div>
<div class="col-md-10">
<h4>End of Workshop</h4>
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</div>
</div>
<!-- End Schdule Day 1 -->
<!-- Schdule Day 2 -->
<!--<div role="tabpanel" class="col-lg-9 tab-pane fade" id="afternoon">
<div class="row schedule-item">
<div class="col-md-2"><time>10:00 AM</time></div>
<div class="col-md-10">
<div class="speaker">
<img src="assets/img/speakers/1.jpg" alt="Brenden Legros">
</div>
<h4>Libero corrupti explicabo itaque. <span>Brenden Legros</span></h4>
<p>Facere provident incidunt quos voluptas.</p>
</div>
</div>
<div class="row schedule-item">
<div class="col-md-2"><time>11:00 AM</time></div>
<div class="col-md-10">
<div class="speaker">
<img src="assets/img/speakers/2.jpg" alt="Hubert Hirthe">
</div>
<h4>Et voluptatem iusto dicta nobis. <span>Hubert Hirthe</span></h4>
<p>Maiores dignissimos neque qui cum accusantium ut sit sint inventore.</p>
</div>
</div>
<div class="row schedule-item">
<div class="col-md-2"><time>12:00 AM</time></div>
<div class="col-md-10">
<div class="speaker">
<img src="assets/img/speakers/3.jpg" alt="Cole Emmerich">
</div>
<h4>Explicabo et rerum quis et ut ea. <span>Cole Emmerich</span></h4>
<p>Veniam accusantium laborum nihil eos eaque accusantium aspernatur.</p>
</div>
</div>
<div class="row schedule-item">
<div class="col-md-2"><time>02:00 PM</time></div>
<div class="col-md-10">
<div class="speaker">
<img src="assets/img/speakers/4.jpg" alt="Jack Christiansen">
</div>
<h4>Qui non qui vel amet culpa sequi. <span>Jack Christiansen</span></h4>
<p>Nam ex distinctio voluptatem doloremque suscipit iusto.</p>
</div>
</div>
<div class="row schedule-item">
<div class="col-md-2"><time>03:00 PM</time></div>
<div class="col-md-10">
<div class="speaker">
<img src="assets/img/speakers/5.jpg" alt="Alejandrin Littel">
</div>
<h4>Quos ratione neque expedita asperiores. <span>Alejandrin Littel</span></h4>
<p>Eligendi quo eveniet est nobis et ad temporibus odio quo.</p>
</div>
</div>
<div class="row schedule-item">
<div class="col-md-2"><time>04:00 PM</time></div>
<div class="col-md-10">
<div class="speaker">
<img src="assets/img/speakers/6.jpg" alt="Willow Trantow">
</div>
<h4>Quo qui praesentium nesciunt <span>Willow Trantow</span></h4>
<p>Voluptatem et alias dolorum est aut sit enim neque veritatis.</p>
</div>
</div>
</div>-->
<!-- End Schdule Day 2 -->
</div>
</div>
</section><!-- End Schedule Section -->
<!-- ======= Supporters Section ======= -->
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<h2>Partners</h2>
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<h2>Contact Us</h2>
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