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update publication links
Added Google Analytics and updated publication links with data attributes for tracking.
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‎index.html‎

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font-size: 0.92rem;
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}
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</style>
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<!-- Google tag (gtag.js) -->
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<script async src="https://www.googletagmanager.com/gtag/js?id=G-GX8QSZTJH6"></script>
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<script>
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window.dataLayer = window.dataLayer || [];
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function gtag(){dataLayer.push(arguments);}
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gtag('js', new Date());
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gtag('config', 'G-GX8QSZTJH6');
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</script>
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</head>
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<body>
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<div class="wrap">
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<!-- Top navigation -->
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<!-- <div class="topbar"> -->
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<!-- <div class="site-title">Yunzhen Yao</div> -->
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<!-- <div class="nav" aria-label="Primary navigation"> -->
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<!-- <a href="#about">About</a> -->
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<!-- <a href="#news">News</a> -->
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<!-- <a href="#publications">Publications</a> -->
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<!-- </div> -->
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<!-- </div> -->
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<!-- Header / Hero -->
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<div class="hero" id="about">
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<div class="avatar" aria-label="Profile photo">
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<!-- Option A (recommended): put a file named avatar.jpg in your repo root and uncomment below -->
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<img src="avatar.jpg" alt="Yunzhen Yao" />
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<!-- Option B: placeholder -->
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<!-- <span class="small">avatar</span> -->
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</div>
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<div>
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</p>
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<div class="linkrow">
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<!-- Replace # with your real links -->
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<a href="https://scholar.google.com/citations?user=Ga00jcIAAAAJ&hl=en" target="_blank" rel="noopener">Google Scholar</a>
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<a href="https://github.com/implicitvalue" target="_blank" rel="noopener">GitHub</a>
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<a href="https://www.linkedin.com/in/yunzhen-yao-18a87a347" target="_blank" rel="noopener">LinkedIn</a>
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<a href="https://dblp.org/pid/284/0567.html" target="_blank" rel="noopener">DBLP</a>
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<a href="https://www.dropbox.com/scl/fi/69alnk06eenydeb179i33/CV_Yunzhen_Yao.pdf?rlkey=2lpg60lr3rsuq41v5f7s9yvh6&st=9tiv2dyy&dl=0">CV</a>
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<a href="https://scholar.google.com/citations?user=Ga00jcIAAAAJ&hl=en"
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target="_blank" rel="noopener"
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data-ga="scholar" data-title="Google Scholar">
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Google Scholar
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</a>
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<a href="https://github.com/implicitvalue"
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target="_blank" rel="noopener"
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data-ga="github" data-title="GitHub Profile">
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GitHub
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</a>
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<a href="https://www.linkedin.com/in/yunzhen-yao-18a87a347"
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target="_blank" rel="noopener"
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data-ga="linkedin" data-title="LinkedIn">
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LinkedIn
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</a>
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<a href="https://dblp.org/pid/284/0567.html"
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target="_blank" rel="noopener"
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data-ga="dblp" data-title="DBLP">
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DBLP
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</a>
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<a href="https://www.dropbox.com/scl/fi/69alnk06eenydeb179i33/CV_Yunzhen_Yao.pdf?rlkey=2lpg60lr3rsuq41v5f7s9yvh6&st=9tiv2dyy&dl=0"
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target="_blank" rel="noopener"
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data-ga="cv" data-title="CV (Dropbox PDF)">
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CV
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</a>
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</div>
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<div class="email">
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<div>
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<section class="research">
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<p>
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I am a fourth-year PhD student at <a href="https://www.epfl.ch/en/" target="_blank" rel="noopener">EPFL</a>, advised by
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Prof. <a href="https://ic-people.epfl.ch/~gastpar/" target="_blank" rel="noopener">Michael Gastpar</a>.
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</p>
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<p>
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My research focuses on the <strong>theoretical foundations and practical methods</strong> for building
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<strong>reliable, trustworthy, and efficient</strong> machine learning systems, with an emphasis on
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<strong>uncertainty quantification</strong> and <strong>robust decision-making</strong>.
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</p>
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<ul>
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<li>Inference-time adaptation for large language models (LLMs)</li>
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<li>Uncertainty quantification for machine learning systems, including conformal prediction</li>
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<li>Preference learning and LLM alignment</li>
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<li>Finite-sample and non-asymptotic analysis of learning algorithms</li>
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</ul>
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<p>
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I am a fourth-year PhD student at
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<a href="https://www.epfl.ch/en/"
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target="_blank" rel="noopener"
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data-ga="affiliation" data-title="EPFL">
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EPFL
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</a>, advised by
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Prof.
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<a href="https://ic-people.epfl.ch/~gastpar/"
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target="_blank" rel="noopener"
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data-ga="person" data-title="Michael Gastpar (advisor)">
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Michael Gastpar
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</a>.
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</p>
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<p>
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My research focuses on the <strong>theoretical foundations and practical methods</strong> for building
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<strong>reliable, trustworthy, and efficient</strong> machine learning systems, with an emphasis on
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<strong>uncertainty quantification</strong> and <strong>robust decision-making</strong>.
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</p>
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<ul>
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<li>Inference-time adaptation for large language models (LLMs)</li>
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<li>Uncertainty quantification for machine learning systems, including conformal prediction</li>
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<li>Preference learning and LLM alignment</li>
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<li>Finite-sample and non-asymptotic analysis of learning algorithms</li>
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</ul>
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</section>
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</div>
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<!-- Publications -->
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<section id="publications">
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<h2>Publications</h2>
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<ul class="pub">
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<li>
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<div class="pub-title">
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<a href="https://arxiv.org/abs/2510.07093" target="_blank" rel="noopener">
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Non-Asymptotic Analysis of Efficiency in Conformalized Regression
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</a>
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</div>
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<div class="pub-meta">
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<em>Yunzhen Yao</em>, Lie He, Michael Gastpar · Preprint
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</div>
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</li>
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<li>
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<div class="pub-title">
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<a href="https://arxiv.org/abs/2506.01084" target="_blank" rel="noopener">
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zip2zip: Inference-Time Adaptive Vocabularies for Language Models via Token Compression
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</a>
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</div>
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<div class="pub-meta">
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Saibo Geng*, Nathan Ranchin*, <em>Yunzhen Yao</em>, Maxime Peyrard,
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Chris Wendler, Michael Gastpar, Robert West · NeurIPS 2025
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</div>
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</li>
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<li>
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<div class="pub-title">
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<a href="https://arxiv.org/abs/2501.18282" target="_blank" rel="noopener">
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Leveraging Sparsity for Sample-Efficient Preference Learning: A Theoretical Perspective
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</a>
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</div>
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<div class="pub-meta">
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<em>Yunzhen Yao</em>, Lie He, Michael Gastpar · ICML 2025
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</div>
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</li>
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<li>
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<div class="pub-title">
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<a href="https://www.jmlr.org/papers/volume25/22-0816/22-0816.pdf" target="_blank" rel="noopener">
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Unlabeled Principal Component Analysis and Matrix Completion
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</a>
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</div>
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<div class="pub-meta">
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<em>Yunzhen Yao</em>, Liangzu Peng, Manolis Tsakiris · JMLR 2024
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</div>
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</li>
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<li>
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<div class="pub-title">
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<a href="https://proceedings.neurips.cc/paper/2021/hash/ff8c1a3bd0c441439a0a081e560c85fc-Abstract.html"
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target="_blank" rel="noopener">
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Unlabeled Principal Component Analysis
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</a>
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</div>
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<div class="pub-meta">
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<em>Yunzhen Yao</em>, Liangzu Peng, Manolis Tsakiris · NeurIPS 2021
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</div>
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</li>
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<li>
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<div class="pub-title">
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<a href="https://ieeexplore.ieee.org/document/9517881/authors#authors"
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target="_blank" rel="noopener">
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Unsigned Matrix Completion
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</a>
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</div>
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<div class="pub-meta">
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<em>Yunzhen Yao</em>, Liangzu Peng, Manolis Tsakiris · ISIT 2021
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</div>
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</li>
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</ol>
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<ul class="pub">
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<li>
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<div class="pub-title">
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<a href="https://arxiv.org/abs/2510.07093"
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target="_blank" rel="noopener"
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data-ga="publication" data-title="Non-Asymptotic Analysis of Efficiency in Conformalized Regression (arXiv)">
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Non-Asymptotic Analysis of Efficiency in Conformalized Regression
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</a>
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</div>
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<div class="pub-meta">
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<em>Yunzhen Yao</em>, Lie He, Michael Gastpar · Preprint
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</div>
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</li>
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<li>
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<div class="pub-title">
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<a href="https://arxiv.org/abs/2506.01084"
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target="_blank" rel="noopener"
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data-ga="publication" data-title="zip2zip (arXiv)">
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zip2zip: Inference-Time Adaptive Vocabularies for Language Models via Token Compression
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</a>
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</div>
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<div class="pub-meta">
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Saibo Geng*, Nathan Ranchin*, <em>Yunzhen Yao</em>, Maxime Peyrard,
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Chris Wendler, Michael Gastpar, Robert West · NeurIPS 2025
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</div>
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</li>
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<li>
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<div class="pub-title">
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<a href="https://arxiv.org/abs/2501.18282"
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target="_blank" rel="noopener"
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data-ga="publication" data-title="Leveraging Sparsity for Sample-Efficient Preference Learning (arXiv)">
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Leveraging Sparsity for Sample-Efficient Preference Learning: A Theoretical Perspective
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</a>
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</div>
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<div class="pub-meta">
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<em>Yunzhen Yao</em>, Lie He, Michael Gastpar · ICML 2025
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</div>
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</li>
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<li>
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<div class="pub-title">
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<a href="https://www.jmlr.org/papers/volume25/22-0816/22-0816.pdf"
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target="_blank" rel="noopener"
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data-ga="publication" data-title="Unlabeled Principal Component Analysis and Matrix Completion (JMLR PDF)">
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Unlabeled Principal Component Analysis and Matrix Completion
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</a>
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</div>
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<div class="pub-meta">
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<em>Yunzhen Yao</em>, Liangzu Peng, Manolis Tsakiris · JMLR 2024
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</div>
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</li>
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<li>
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<div class="pub-title">
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<a href="https://proceedings.neurips.cc/paper/2021/hash/ff8c1a3bd0c441439a0a081e560c85fc-Abstract.html"
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target="_blank" rel="noopener"
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data-ga="publication" data-title="Unlabeled Principal Component Analysis (NeurIPS 2021)">
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Unlabeled Principal Component Analysis
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</a>
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</div>
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<div class="pub-meta">
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<em>Yunzhen Yao</em>, Liangzu Peng, Manolis Tsakiris · NeurIPS 2021
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</div>
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</li>
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<li>
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<div class="pub-title">
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<a href="https://ieeexplore.ieee.org/document/9517881/authors#authors"
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target="_blank" rel="noopener"
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data-ga="publication" data-title="Unsigned Matrix Completion (ISIT 2021)">
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Unsigned Matrix Completion
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</a>
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</div>
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<div class="pub-meta">
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<em>Yunzhen Yao</em>, Liangzu Peng, Manolis Tsakiris · ISIT 2021
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</div>
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</li>
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</ul>
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</section>
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<footer>
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</script>
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</footer>
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</div>
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