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<h2>LIPIcs, Volume 156, FORC 2020</h2>
<ul>
<li>
    <span class="authors">Aaron Roth</span>
    <span class="title">LIPIcs, Volume 156, FORC 2020, Complete Volume</span>
    <a class="doi" href="https://doi.org/10.4230/LIPIcs.FORC.2020">10.4230/LIPIcs.FORC.2020</a>
</li>
<li>
    <span class="authors">Aaron Roth</span>
    <span class="title">Front Matter, Table of Contents, Preface, Conference Organization</span>
    <a class="doi" href="https://doi.org/10.4230/LIPIcs.FORC.2020.0">10.4230/LIPIcs.FORC.2020.0</a>
</li>
<li>
    <span class="authors">Lee Cohen, Zachary C. Lipton, and Yishay Mansour</span>
    <span class="title">Efficient Candidate Screening Under Multiple Tests and Implications for Fairness</span>
    <a class="doi" href="https://doi.org/10.4230/LIPIcs.FORC.2020.1">10.4230/LIPIcs.FORC.2020.1</a>
</li>
<li>
    <span class="authors">Christina Ilvento</span>
    <span class="title">Metric Learning for Individual Fairness</span>
    <a class="doi" href="https://doi.org/10.4230/LIPIcs.FORC.2020.2">10.4230/LIPIcs.FORC.2020.2</a>
</li>
<li>
    <span class="authors">Avrim Blum and Kevin Stangl</span>
    <span class="title">Recovering from Biased Data: Can Fairness Constraints Improve Accuracy?</span>
    <a class="doi" href="https://doi.org/10.4230/LIPIcs.FORC.2020.3">10.4230/LIPIcs.FORC.2020.3</a>
</li>
<li>
    <span class="authors">Moni Naor and Neil Vexler</span>
    <span class="title">Can Two Walk Together: Privacy Enhancing Methods and Preventing Tracking of Users</span>
    <a class="doi" href="https://doi.org/10.4230/LIPIcs.FORC.2020.4">10.4230/LIPIcs.FORC.2020.4</a>
</li>
<li>
    <span class="authors">Christopher Jung, Sampath Kannan, and Neil Lutz</span>
    <span class="title">Service in Your Neighborhood: Fairness in Center Location</span>
    <a class="doi" href="https://doi.org/10.4230/LIPIcs.FORC.2020.5">10.4230/LIPIcs.FORC.2020.5</a>
</li>
<li>
    <span class="authors">Ashesh Rambachan and Jonathan Roth</span>
    <span class="title">Bias In, Bias Out? Evaluating the Folk Wisdom</span>
    <a class="doi" href="https://doi.org/10.4230/LIPIcs.FORC.2020.6">10.4230/LIPIcs.FORC.2020.6</a>
</li>
<li>
    <span class="authors">Cynthia Dwork, Christina Ilvento, and Meena Jagadeesan</span>
    <span class="title">Individual Fairness in Pipelines</span>
    <a class="doi" href="https://doi.org/10.4230/LIPIcs.FORC.2020.7">10.4230/LIPIcs.FORC.2020.7</a>
</li>
<li>
    <span class="authors">Cynthia Dwork, Christina Ilvento, Guy N. Rothblum, and Pragya Sur</span>
    <span class="title">Abstracting Fairness: Oracles, Metrics, and Interpretability</span>
    <a class="doi" href="https://doi.org/10.4230/LIPIcs.FORC.2020.8">10.4230/LIPIcs.FORC.2020.8</a>
</li>
<li>
    <span class="authors">Mark Braverman and Sumegha Garg</span>
    <span class="title">The Role of Randomness and Noise in Strategic Classification</span>
    <a class="doi" href="https://doi.org/10.4230/LIPIcs.FORC.2020.9">10.4230/LIPIcs.FORC.2020.9</a>
</li>
<li>
    <span class="authors">Katrina Ligett, Charlotte Peale, and Omer Reingold</span>
    <span class="title">Bounded-Leakage Differential Privacy</span>
    <a class="doi" href="https://doi.org/10.4230/LIPIcs.FORC.2020.10">10.4230/LIPIcs.FORC.2020.10</a>
</li>
</ul>

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