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<!DOCTYPE html>
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<title>Decentralization and Trustworthy Machine Learning in Web3: Methodologies, Platforms, and Applications | Workshop at NeurIPS 2022</title>
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<h1 class="project-name">Decentralization and Trustworthy Machine Learning in Web3: <br> Methodologies, Platforms, and Applications</h1>
<h2 class="project-tagline">Workshop at <a href="https://neurips.cc/">NeurIPS 2022</a><br> In-person, December 3, 2022</h2>
<a href="/DMLW2022/" class="btn">Home</a>
<a href="/DMLW2022/cfp" class="btn">Call for Papers</a>
<a href="/DMLW2022/papers" class="btn">Accepted Papers</a>
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<h2>Best Paper Award</h2>
<ol>
<li><b><a href="/DMLW2022/assets/papers/3.pdf">Bayesian-Nash-Incentive-Compatible Mechanism for Blockchain Transaction Fee Allocation</a></b> <br />Zishuo Zhao, Xi Chen, Yuan Zhou </li>
</ol>
<h2>Runner-up Award</h2>
<ol>
<li><b><a href="/DMLW2022/assets/papers/5.pdf">FLock: Defending Malicious Behaviors in Federated Learning with Blockchain</a></b> <br />Nanqing Dong, Jiahao Sun, Zhipeng Wang, Shuoying Zhang, Shuhao Zheng </li>
<li><b><a href="/DMLW2022/assets/papers/9.pdf">Scalable Collaborative Learning via Representation Sharing</a></b> <br />Frédéric Berdoz, Abhishek Singh, Martin Jaggi, Ramesh Raskar </li>
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<h2 id="accepted-papers">All Accepted Papers</h2>
<!-- <h4>This list will be updated based on the metadata of each paper after the camera-ready deadline.</h4>-->
<h4>All accepted papers will have a poster presentation and a SlidesLive video. Please check our workshop page for more details:
<a href="https://nips.cc/virtual/2022/workshop/50001">https://nips.cc/virtual/2022/workshop/50001</a>.</h4>
<ol>
<!-- <li><b>Improving Fairness in Image Classification via Sketching</b> <br /> Ruichen Yao; Ziteng Cui; Xiaoxiao Li; Lin Gu</li>-->
<li><b><a href="/DMLW2022/assets/papers/0.pdf">A Blockchain Protocol for Human-in-the-Loop AI</a></b> <br /> Nassim Dehouche, Richard Blythman </li>
<li><b><a href="/DMLW2022/assets/papers/1.pdf">A Secure Aggregation for Federated Learning on Long-Tailed Data</a></b> <br />Yanna Jiang, Baihe Ma, Xu Wang, Guangsheng Yu, Caijun Sun, Wei Ni, Ren Ping Liu </li>
<li><b><a href="/DMLW2022/assets/papers/2.pdf">Addressing bias in Face Detectors using Decentralised Data collection with incentives</a></b> <br />Ahan M R, Robin Lehmann, Richard Blythman </li>
<li><b><a href="/DMLW2022/assets/papers/3.pdf">Bayesian-Nash-Incentive-Compatible Mechanism for Blockchain Transaction Fee Allocation</a></b> <br />Zishuo Zhao, Xi Chen, Yuan Zhou </li>
<li><b><a href="/DMLW2022/assets/papers/4.pdf">Communication-efficient Decentralized Deep Learning</a></b> <br />Fateme Fotouhi, Aditya Balu, Zhanhong Jiang, Yasaman Esfandiari, Salman Jahani, Soumik Sarkar </li>
<li><b><a href="/DMLW2022/assets/papers/5.pdf">FLock: Defending Malicious Behaviors in Federated Learning with Blockchain</a></b> <br />Nanqing Dong, Jiahao Sun, Zhipeng Wang, Shuoying Zhang, Shuhao Zheng </li>
<li><b><a href="/DMLW2022/assets/papers/6.pdf">Incentivizing Intelligence: The Bittensor Approach</a></b> <br />Jacob Steeves, Ala Shaabana, Yuqian Hu, Francois Luus, Sin Tai Liu, Jacqueline Dawn Tasker-Steeves </li>
<li><b><a href="/DMLW2022/assets/papers/7.pdf">Modulus: An Open Modular Design for Interoperable and Reusable Machine Learning</a></b> <br />Salvatore Vivona, Luca Vivona </li>
<li><b><a href="/DMLW2022/assets/papers/8.pdf">Opportunities for Decentralized Technologies within AI Hubs</a></b> <br />Richard Blythman, Mohamed Arshath, Salvatore Vivona, Jakub Smékal, Hithesh Shaji </li>
<li><b><a href="/DMLW2022/assets/papers/9.pdf">Scalable Collaborative Learning via Representation Sharing</a></b> <br />Frédéric Berdoz, Abhishek Singh, Martin Jaggi, Ramesh Raskar </li>
<li><b><a href="/DMLW2022/assets/papers/10.pdf">Simulations for Open Science Token Communities: Designing the Knowledge Commons</a></b> <br />Shady El Damaty, Jakub Smékal </li>
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