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  <title>Software — Azadeh Khaleghi</title>
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      <h1>Azadeh Khaleghi</h1>
      <p>Professor of Statistics (HDR equiv.) —
        <a href="https://www.ensae.fr">ENSAE</a> -
        <a href="https://crest.science">CREST</a>, IP Paris
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      <p class="lead">Research Interests: statistical learning theory, information theory, nonparametric statistics, long-memory processes</p>
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        <div class="section-title"><h2>Software & Code</h2></div>
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            <li><b>A. Khaleghi</b>, <a href = "https://lukaszierahn.github.io">L. Zierahn</a>, <a href="https://cran.r-project.org/web/packages/RChest/index.html"><i>RChest</i></a> and <a href="https://pypi.org/project/PyChest/"><i>PyChest</i></a>: An <b>R</b> package available on CRAN, (respectively a <b>Python</b> Package available on PyPi) for locating distributional changes in piece-wise stationary timeseries with long-range dependencies, (2021).
              <ul>
                <li><i>Corresponding Paper: <b>A. Khaleghi</b>, L. Zierahn, <a href="https://arxiv.org/abs/2112.10565">PyChEst: a Python package for the consistent retrospective estimation of distributional changes in piece-wise stationary time series</a>, arXiv:2112.10565.</i></li>
                <li><i>The <a href="https://github.com/azalk/GoChest">Github repository</a> contains a <b>Go</b> implementation which is also interfaced with <b>Python</b>.</i></li>
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            <li><p><a href="https://github.com/azalk/Oblivious">Github repository</a> for the implementation of our Algorithmically Fair Classification and Regression methods proposed in <a href="https://arxiv.org/abs/2002.02901">this paper</a>.</p></li>
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