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kitsuya0828 committed Feb 2, 2024
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198 changes: 198 additions & 0 deletions index.html
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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta name="description"
content="">
<meta name="keywords" content="Federated Learning, Knowledge Distillation, Out-of-Distribution Detection">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>Energy-based Knowledge Distillation for Communication-Efficient Federated Learning</title>

<link href="https://fonts.googleapis.com/css?family=Google+Sans|Noto+Sans|Castoro"
rel="stylesheet">

<link rel="stylesheet" href="./static/css/bulma.min.css">
<link rel="stylesheet" href="./static/css/fontawesome.all.min.css">
<link rel="stylesheet"
href="https://cdn.jsdelivr.net/gh/jpswalsh/academicons@1/css/academicons.min.css">
<link rel="stylesheet" href="./static/css/index.css">
<link rel="icon" href="./static/images/favicon.svg">

<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.5.1/jquery.min.js"></script>
<script defer src="./static/js/fontawesome.all.min.js"></script>
<script src="./static/js/index.js"></script>
</head>
<body>

<nav class="navbar" role="navigation" aria-label="main navigation">
<div class="navbar-brand">
<a role="button" class="navbar-burger" aria-label="menu" aria-expanded="false">
<span aria-hidden="true"></span>
<span aria-hidden="true"></span>
<span aria-hidden="true"></span>
</a>
</div>
<div class="navbar-menu">
<div class="navbar-start" style="flex-grow: 1; justify-content: center;">
<a class="navbar-item" href="https://azu-kitsu.com">
<span class="icon">
<i class="fas fa-home"></i>
</span>
</a>

<div class="navbar-item has-dropdown is-hoverable">
<a class="navbar-link">
More Research
</a>
<div class="navbar-dropdown">
<a class="navbar-item" href="/">
DSFL+
</a>
</div>
</div>
</div>

</div>
</nav>


<section class="hero">
<div class="hero-body">
<div class="container is-max-desktop">
<div class="columns is-centered">
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<h1 class="title is-1 publication-title">Energy-based Knowledge Distillation for Communication-Efficient Federated Learning</h1>
<div class="is-size-5 publication-authors">
<span class="author-block">
<a href="https://azu-kitsu.com">Kitsuya Azuma</a><sup>1</sup>,</span>
<span class="author-block">
<a href="https://researchmap.jp/tomo_miyazaki">Tomo Miyazaki</a><sup>2</sup>,</span>
<span class="author-block">
<a href="https://researchmap.jp/read0180306">Shinichiro Omachi</a><sup>2</sup>,
</span>
</div>

<div class="is-size-5 publication-authors">
<span class="author-block"><sup>1</sup>School of Engineering, Tohoku University,</span>
<span class="author-block"><sup>2</sup>Graduate School of Engineering, Tohoku University</span>
</div>

<div class="column has-text-centered">
<div class="publication-links">
<!-- Code Link. -->
<span class="link-block">
<a href="https://github.com/Kitsuya0828/DSFLplus"
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="fab fa-github"></i>
</span>
<span>Code</span>
</a>
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</div>
</div>
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</div>
</section>


<section class="section">
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<!-- Abstract. -->
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<h2 class="title is-3">Abstract</h2>
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<p>
Federated Learning (FL) is a decentralized machine learning setting where many devices collaboratively train a global model without exposing their local training data. While the most used FL methods average clients' model parameters, several distillation-based methods have been proposed to aggregate model outputs for open unlabeled datasets and transfer the knowledge, which can significantly reduce the communication costs.
</p>
<p>
In this study, we propose a new distillation-based method called DS-FL+, which focus on Energy score. The proposed method utilizes the Energy score used for out-of-distribution detection to perform thresholding, so that clients only send predictions to the server for relatively well-trained data. Further experiments were conducted under two different Non-IID settings to investigate the relationship between threshold value and convergence speed.
</p>
<p>
Experimental results demonstrate our proposed DS-FL+ dramatically reduces the communication costs while accelerating the learning convergence under Non-IID settings.
</p>
</div>
</div>
</div>
<!--/ Abstract. -->
</div>
</section>

<section class="section">
<div class="container is-max-desktop">
<!-- Abstract. -->
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<h2 class="title is-3">Method</h2>
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<p>
To be written.
</p>
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</div>
<!--/ Abstract. -->
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</section>

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<h2 class="title is-3">Results</h2>
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<p>
To be written.
</p>
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</div>
</div>
<!--/ Abstract. -->
</div>
</section>


<!--
<section class="section" id="BibTeX">
<div class="container is-max-desktop content">
<h2 class="title">BibTeX</h2>
<pre><code>@article{park2021nerfies,
author = {Park, Keunhong and Sinha, Utkarsh and Barron, Jonathan T. and Bouaziz, Sofien and Goldman, Dan B and Seitz, Steven M. and Martin-Brualla, Ricardo},
title = {Nerfies: Deformable Neural Radiance Fields},
journal = {ICCV},
year = {2021},
}</code></pre>
</div>
</section> -->


<footer class="footer">
<div class="container">
<div class="content has-text-centered">
<!-- <a class="icon-link"
href="./static/videos/nerfies_paper.pdf">
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</a> -->
<a class="icon-link" href="https://github.com/Kitsuya0828" class="external-link" disabled>
<i class="fab fa-github"></i>
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<div class="column is-8">
<div class="content">
<p>
Thanks to <a href="https://github.com/nerfies/nerfies.github.io">Park, Keunhong</a> for the website template.
</p>
</div>
</div>
</div>
</div>
</footer>

</body>
</html>
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body {
font-family: 'Noto Sans', sans-serif;
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