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| {% if post.id %} | ||
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| <div class="row mb-5 mt-3"> | ||
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| <div class="card text-center shadow p-3 bg-light rounded h-100" id="pinfo"> | ||
| <a href="https://sites.google.com/view/teddy-lfwu/"> | ||
| </a><div class="text-muted"><a href="https://sites.google.com/view/teddy-lfwu/"> | ||
| <img src="static/images/lingfei.jpeg" class="rounded" style="height: 150px;"> | ||
| <h5 class="card-title" align="center">Lingfei Wu</h5> | ||
| </a><div><a href="https://sites.google.com/view/teddy-lfwu/"> | ||
| </a> | ||
| <h6 class="card-subtitle text-muted"> | ||
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| <div class="col-md-3 col-xs-6"> | ||
| <div class="card text-center shadow p-3 bg-light rounded h-100" id="pinfo"> | ||
| <a href="http://pengcui.thumedialab.com/"> | ||
| </a><div class="text-muted"><a href="http://pengcui.thumedialab.com/"> | ||
| <img src="static/images/pengcui.jpeg" class="rounded" style="height: 150px;"> | ||
| <h5 class="card-title" align="center">Peng Cui</h5> | ||
| </a><div><a href="http://pengcui.thumedialab.com/"> | ||
| </a> | ||
| <h6 class="card-subtitle text-muted"> | ||
| Tsinghua University | ||
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| <div class="col-md-3 col-xs-6"> | ||
| <div class="card text-center shadow p-3 bg-light rounded h-100" id="pinfo"> | ||
| <a href="https://www.sfu.ca/computing/people/faculty/jianpei.html"> | ||
| </a><div class="text-muted"><a href="https://www.sfu.ca/computing/people/faculty/jianpei.html"> | ||
| <img src="static/images/jianpei.jpeg" class="rounded" style="height: 150px;"> | ||
| <h5 class="card-title" align="center">Jian Pei</h5> | ||
| </a><div><a href="https://www.sfu.ca/computing/people/faculty/jianpei.html"> | ||
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| Duke University | ||
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| <div class="col-md-3 col-xs-6"> | ||
| <div class="card text-center shadow p-3 bg-light rounded h-100" id="pinfo"> | ||
| <a href="http://cs.emory.edu/~lzhao41/index.htm"> | ||
| </a><div class="text-muted"><a href="http://cs.emory.edu/~lzhao41/index.htm"> | ||
| <img src="static/images/liangzhao.jpeg" class="rounded" style="height: 150px;"> | ||
| <h5 class="card-title" align="center">Liang Zhao</h5> | ||
| </a><div><a href="http://cs.emory.edu/~lzhao41/index.htm"> | ||
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| <h6 class="card-subtitle text-muted"> | ||
| Emory University | ||
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| {% include base_path %} | ||
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| {% if post.header.teaser %} | ||
| {% capture teaser %}{{ post.header.teaser }}{% endcapture %} | ||
| {% else %} | ||
| {% assign teaser = site.teaser %} | ||
| {% endif %} | ||
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| {% if post.id %} | ||
| {% assign title = post.title | markdownify | remove: "<p>" | remove: "</p>" %} | ||
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| <div class="{{ include.type | default: "list" }}__item"> | ||
| <article class="archive__item" itemscope itemtype="http://schema.org/CreativeWork"> | ||
| <p style="font-family:Times New Roman;font-size:110%;margin-bottom:1px;"><b>• Probably Approximately Correct Federated Learning</b></p> | ||
| <p style="font-family:Times New Roman;margin-top:1px;"> Authors: Xiaojin Zhang, <i><b>Anbu Huang</b></i>, Lixin Fan, Kai Chen, Qiang Yang<br> ArXiv Preprint; under review in <a href="https://www.jmlr.org/" target="_blank">Journal of Machine Learning Research (JMLR)</a>, 2023<br> [<a href="https://arxiv.org/pdf/2304.04641.pdf" target="_blank"><i class="fas fa-file-pdf" style="font-size: 0.8em;"></i> Paper</a>]</p> | ||
| </article> | ||
| </div> | ||
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| <div class="{{ include.type | default: "list" }}__item"> | ||
| <article class="archive__item" itemscope itemtype="http://schema.org/CreativeWork"> | ||
| <p style="font-family:Times New Roman;font-size:110%;margin-bottom:1px;"><b>• Federated Learning with Privacy-preserving and Model IP-right-Protection</b></p> | ||
| <p style="font-family:Times New Roman;margin-top:1px;"> Authors: Qiang Yang, <i><b>Anbu Huang</b></i>, Lixin Fan, Chee Seng Chan, Jian Han Lim, Kam Woh Ng, Ding Sheng Ong, Bowen Li<br> Published in <a href="https://link.springer.com/article/10.1007/s11633-022-1343-2" target="_blank">Machine Intelligence Research</a>, 2022<br> [<a href="https://link.springer.com/content/pdf/10.1007/s11633-022-1343-2.pdf" target="_blank"><i class="fas fa-file-pdf" style="font-size: 0.8em;"></i> Paper</a>] [<a href="https://scholar.google.com/citations?view_op=view_citation&hl=en&user=Luv9JqgAAAAJ&citation_for_view=Luv9JqgAAAAJ:W7OEmFMy1HYC" target="_blank"><i class="fas fa-fw fa-graduation-cap" style="font-size: 0.8em;"></i> Scholar</a>] [<a rel="noreferrer noopener" href="https://innovation-cat.github.io/files/bib/fl-ipr.html" target="_blank"><i class="fas fa-quote-right" style="font-size: 0.6em;"></i> Cite</a>]</p> | ||
| </article> | ||
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| <div class="{{ include.type | default: "list" }}__item"> | ||
| <article class="archive__item" itemscope itemtype="http://schema.org/CreativeWork"> | ||
| <p style="font-family:Times New Roman;font-size:110%;margin-bottom:1px;"><b>• StarFL: Hybrid Federated Learning Architecture for Smart Urban Computing</b></p> | ||
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| <p style="font-family:Times New Roman;margin-top:1px;"> Authors: <i><b>Anbu Huang</b></i>, Yang Liu, Tianjian Chen, Yongkai Zhou, Quan Sun, Hongfeng Chai, Qiang Yang<br> Published in <a href="https://dl.acm.org/doi/10.1145/3467956" target="_blank">ACM Transactions on Intelligent Systems and Technology (ACM TIST)</a>, 2021<br> [<a href="https://dl.acm.org/doi/10.1145/3467956" target="_blank"><i class="fas fa-file-pdf" style="font-size: 0.8em;"></i> Paper</a>] [<a href="https://scholar.google.com/citations?view_op=view_citation&hl=en&user=Luv9JqgAAAAJ&citation_for_view=Luv9JqgAAAAJ:UeHWp8X0CEIC" target="_blank"><i class="fas fa-fw fa-graduation-cap" style="font-size: 0.8em;"></i> Scholar</a>] [<a rel="noreferrer noopener" href="https://innovation-cat.github.io/files/bib/starfl_bib.html" target="_blank"><i class="fas fa-quote-right" style="font-size: 0.6em;"></i> Cite</a>]</p> | ||
| </article> | ||
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| <div class="{{ include.type | default: "list" }}__item"> | ||
| <article class="archive__item" itemscope itemtype="http://schema.org/CreativeWork"> | ||
| <p style="font-family:Times New Roman;font-size:110%;margin-bottom:1px;"><b>• Federated Learning-Powered Visual Object Detection for Safety Monitoring</b></p> | ||
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| <p style="font-family:Times New Roman;margin-top:1px;"> Authors: Yang Liu, <i><b>Anbu Huang</b></i>, Yun Luo, He Huang, Youzhi Liu, Yuanyuan Chen, Lican Feng, Tianjian Chen, Han Yu, Qiang Yang<br> Published in <a href="https://ojs.aaai.org/index.php/aimagazine/article/view/15095" target="_blank">AI Magazine</a>, 2021<br> [<a href="https://ojs.aaai.org/index.php/aimagazine/article/download/15095/18864" target="_blank"><i class="fas fa-file-pdf" style="font-size: 0.8em;"></i> Paper</a>] [<a href="https://scholar.google.com/citations?view_op=view_citation&hl=en&user=Luv9JqgAAAAJ&sortby=pubdate&citation_for_view=Luv9JqgAAAAJ:IjCSPb-OGe4C" target="_blank"><i class="fas fa-fw fa-graduation-cap" style="font-size: 0.8em;"></i> Scholar</a>] [<a rel="noreferrer noopener" href="https://innovation-cat.github.io/files/bib/flpower_bib.html" target="_blank"><i class="fas fa-quote-right" style="font-size: 0.6em;"></i> Cite</a>]</p> | ||
| </article> | ||
| </div> | ||
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| <div class="{{ include.type | default: "list" }}__item"> | ||
| <article class="archive__item" itemscope itemtype="http://schema.org/CreativeWork"> | ||
| <p style="font-family:Times New Roman;font-size:110%;margin-bottom:1px;"><b>• Dynamic backdoor attacks against federated learning</b></p> | ||
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| <p style="font-family:Times New Roman;margin-top:1px;"> Authors: <i><b>Anbu Huang</b></i><br> Published in <a href="https://arxiv.org/abs/2011.07429" target="_blank">ArXiv Preprint</a>, 2021<br> [<a href="https://arxiv.org/pdf/2011.07429.pdf" target="_blank"><i class="fas fa-file-pdf" style="font-size: 0.8em;"></i> Paper</a>] [<a href="https://scholar.google.com/citations?view_op=view_citation&hl=en&user=Luv9JqgAAAAJ&sortby=pubdate&citation_for_view=Luv9JqgAAAAJ:qjMakFHDy7sC" target="_blank"><i class="fas fa-fw fa-graduation-cap" style="font-size: 0.8em;"></i> Scholar</a>] [<a rel="noreferrer noopener" href="https://innovation-cat.github.io/files/bib/dynamic_bib.html" target="_blank"><i class="fas fa-quote-right" style="font-size: 0.6em;"></i> Cite</a>]</p> | ||
| </article> | ||
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| <div class="{{ include.type | default: "list" }}__item"> | ||
| <article class="archive__item" itemscope itemtype="http://schema.org/CreativeWork"> | ||
| <p style="font-family:Times New Roman;font-size:110%;margin-bottom:1px;"><b>• Fedvision: An online visual object detection platform powered by federated learning</b></p> | ||
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| <p style="font-family:Times New Roman;margin-top:1px;"> Authors: Yang Liu, <i><b>Anbu Huang</b></i>, Yun Luo, He Huang, Youzhi Liu, Yuanyuan Chen, Lican Feng, Tianjian Chen, Han Yu, Qiang Yang<br> Published in <a href="https://ojs.aaai.org//index.php/AAAI/article/view/7021" target="_blank">Proceedings of the AAAI Conference on Artificial Intelligence</a>, 2020<br> [<a href="https://arxiv.org/pdf/2001.06202.pdf" target="_blank"><i class="fas fa-file-pdf" style="font-size: 0.8em;"></i> Paper</a>] [<a href="https://scholar.google.com/citations?view_op=view_citation&hl=en&user=Luv9JqgAAAAJ&sortby=pubdate&citation_for_view=Luv9JqgAAAAJ:d1gkVwhDpl0C" target="_blank"><i class="fas fa-fw fa-graduation-cap" style="font-size: 0.8em;"></i> Scholar</a>] [<a href="https://innovation-cat.github.io/files/IAAI2020.pdf" target="_blank"><i class="fas fa-file-powerpoint" style="font-size: 0.8em;"></i> Slide</a>] [<a rel="noreferrer noopener" href="https://innovation-cat.github.io/files/bib/fedvision_bib.html" target="_blank"><i class="fas fa-quote-right" style="font-size: 0.6em;"></i> Cite</a>] [<a href="https://github.com/FederatedAI/FedVision" target="_blank"><i class="fas fa-code" style="font-size: 0.8em;"></i> Code</a>]</p> | ||
| </article> | ||
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| <div class="{{ include.type | default: "list" }}__item"> | ||
| <article class="archive__item" itemscope itemtype="http://schema.org/CreativeWork"> | ||
| <p style="font-family:Times New Roman;font-size:110%;margin-bottom:1px;"><b>• RPN: A residual pooling network for efficient federated learning</b></p> | ||
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| <p style="font-family:Times New Roman;margin-top:1px;"> Authors: <i><b>Anbu Huang</b></i>, Yuanyuan Chen, Yang Liu, Tianjian Chen, Qiang Yang<br> Published in <a href="http://ecai2020.eu/" target="_blank">European Conference on Artificial Intelligence (ECAI)</a>, 2020<br> [<a href="http://ecai2020.eu/papers/551_paper.pdf" target="_blank"><i class="fas fa-file-pdf" style="font-size: 0.8em;"></i> Paper</a>] [<a href="https://scholar.google.com/citations?view_op=view_citation&hl=en&user=Luv9JqgAAAAJ&sortby=pubdate&citation_for_view=Luv9JqgAAAAJ:9yKSN-GCB0IC" target="_blank"><i class="fas fa-fw fa-graduation-cap" style="font-size: 0.8em;"></i> Scholar</a>] [<a rel="noreferrer noopener" href="https://innovation-cat.github.io/files/bib/rpn_bib.html" target="_blank"><i class="fas fa-quote-right" style="font-size: 0.6em;"></i> Cite</a>]</p> | ||
| </article> | ||
| </div> | ||
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| <div class="{{ include.type | default: "list" }}__item"> | ||
| <article class="archive__item" itemscope itemtype="http://schema.org/CreativeWork"> | ||
| <p style="font-family:Times New Roman;font-size:110%;margin-bottom:1px;"><b>• SolarNet: A Deep Learning Framework to Map Solar Plants In China From Satellite Imagery</b></p> | ||
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| <p style="font-family:Times New Roman;margin-top:1px;"> Authors: Xin Hou, Biao Wang, Wanqi Hu, Lei Yin, <i><b>Anbu Huang</b></i>, Haishan Wu<br> Published in <a href="https://www.climatechange.ai/papers/iclr2020/6" target="_blank">ICLR 2020 Workshop on Tackling Climate Change with Machine Learning</a>, 2020<br> [<a href="https://s3.us-east-1.amazonaws.com/climate-change-ai/papers/iclr2020/6/paper.pdf" target="_blank"><i class="fas fa-file-pdf" style="font-size: 0.8em;"></i> Paper</a>] [<a href="https://scholar.google.com/citations?view_op=view_citation&hl=en&user=Luv9JqgAAAAJ&sortby=pubdate&citation_for_view=Luv9JqgAAAAJ:2osOgNQ5qMEC" target="_blank"><i class="fas fa-fw fa-graduation-cap" style="font-size: 0.8em;"></i> Scholar</a>] [<a href="https://innovation-cat.github.io/files/solarnet.pdf" target="_blank"><i class="fas fa-file-powerpoint" style="font-size: 0.8em;"></i> Slide</a>] [<a href="https://slideslive.com/38926233/solarnet-a-deep-learning-framework-to-map-solar-plants-in-china-from-satellite-imagery" target="_blank"><i class="fas fa-video" style="font-size: 0.8em;"></i> Video</a>] [<a rel="noreferrer noopener" href="https://innovation-cat.github.io/files/bib/solarnet_bib.html" target="_blank"><i class="fas fa-quote-right" style="font-size: 0.6em;"></i> Cite</a>]</p> | ||
| </article> | ||
| </div> | ||
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| <div class="{{ include.type | default: "list" }}__item"> | ||
| <article class="archive__item" itemscope itemtype="http://schema.org/CreativeWork"> | ||
| <p style="font-family:Times New Roman;font-size:110%;margin-bottom:1px;"><b>• Privacy-preserving heterogeneous federated transfer learning</b></p> | ||
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| <p style="font-family:Times New Roman;margin-top:1px;"> Authors: Dashan Gao, Yang Liu, <i><b>Anbu Huang</b></i>, Ce Ju, Han Yu, Qiang Yang<br> Published in <a href="https://www.computer.org/csdl/proceedings-article/big-data/2019/09005992/1hJrNyyOxyM" target="_blank">IEEE International Conference on Big Data (Big Data)</a>, 2019<br> [<a href="https://www.computer.org/csdl/proceedings-article/big-data/2019/09005992/1hJrNyyOxyM" target="_blank"><i class="fas fa-file-pdf" style="font-size: 0.8em;"></i> Paper</a>] [<a href="https://scholar.google.com/citations?view_op=view_citation&hl=en&user=Luv9JqgAAAAJ&sortby=pubdate&citation_for_view=Luv9JqgAAAAJ:u5HHmVD_uO8C" target="_blank"><i class="fas fa-fw fa-graduation-cap" style="font-size: 0.8em;"></i> Scholar</a>] [<a rel="noreferrer noopener" href="https://innovation-cat.github.io/files/bib/pphtfl_bib.html" target="_blank"><i class="fas fa-quote-right" style="font-size: 0.6em;"></i> Cite</a>]</p> | ||
| </article> | ||
| </div> | ||
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| <div class="{{ include.type | default: "list" }}__item"> | ||
| <article class="archive__item" itemscope itemtype="http://schema.org/CreativeWork"> | ||
| <p style="font-family:Times New Roman;font-size:110%;margin-bottom:1px;"><b>• Real-world image datasets for federated learning</b></p> | ||
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| <p style="font-family:Times New Roman;margin-top:1px;"> Authors: Jiahuan Luo, Xueyang Wu, Yun Luo, <i><b>Anbu Huang</b></i>, Yunfeng Huang, Yang Liu, Qiang Yang<br> Published in <a href="https://federated-learning.org/fl-neurips-2019/" target="_blank">NeurIPS Workshop on Federated Learning for Data Privacy and Confidentiality</a>, 2019<br> [<a href="https://arxiv.org/pdf/1910.11089.pdf" target="_blank"><i class="fas fa-file-pdf" style="font-size: 0.8em;"></i> Paper</a>] [<a href="https://scholar.google.com/citations?view_op=view_citation&hl=en&user=Luv9JqgAAAAJ&sortby=pubdate&citation_for_view=Luv9JqgAAAAJ:u-x6o8ySG0sC" target="_blank"><i class="fas fa-fw fa-graduation-cap" style="font-size: 0.8em;"></i> Scholar</a>] [<a rel="noreferrer noopener" href="https://innovation-cat.github.io/files/bib/dataset_bib.html" target="_blank"><i class="fas fa-quote-right" style="font-size: 0.6em;"></i> Cite</a>] [<a href="https://github.com/jiahuanluo/Federated-Benchmark" target="_blank"><i class="fas fa-code" style="font-size: 0.8em;"></i> Code</a>]</p> | ||
| </article> | ||
| </div> |
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| --- | ||
| layout: archive | ||
| title: "作者信息" | ||
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| {% include archive-single-authors.html %} | ||
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| --- | ||
| layout: archive | ||
| title: "学习资源与习题" | ||
| permalink: /Resource/ | ||
| author_profile: true | ||
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| {% include base_path %} | ||
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