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Full Publications.html
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<title>Xingyu Zhao @ PALM, SEU</title>
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<table summary="Table for page layout." id="tlayout">
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<td id="layout-menu">
<div class="menu-category">Links</div>
<div class="menu-item"><a href="http://palm.seu.edu.cn/" target="blank">PALM Lab</a></div>
<div class="menu-item"><a href="http://palm.seu.edu.cn/members.html" target="blank">PALM Members</a>
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<div class="menu-item"><a href="https://www.seu.edu.cn">Southeast University</a></div>
<div class="menu-category">Pages</div>
<div class="menu-item"><a href="index.html">Homepage</a></div>
<div class="menu-item"><a href="Academic Services.html">Academic Services</a></div>
<div class="menu-item"><a href="Full Publications.html">Full Publications</a></div>
<div class="menu-item"><a href="https://dblp.uni-trier.de/pid/83/504-2.html" target="blank">DBLP</a></div>
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<a href="http://scholar.google.com/citations?user=JkOe0rEAAAAJ&hl=en"
target="blank">Google Scholar</a>
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<div id="toptitle">
<h1>Full Publications</h1></div>
<h3>Journal Articles </h3>
<ul>
<li>
<p>Yuexuan An, Hui Xue, <strong>Xingyu Zhao</strong>, Ning Xu, Pengfei Fang, Xin Geng. Leveraging
Bilateral Correlations for Multi-Label Few-Shot Learning. IEEE Transactions on Neural Networks
and Learning Systems (TNNLS), 2024, in press.</p></li>
<li>
<p><strong>Xingyu Zhao</strong>, Yuexuan An, Ning Xu, Xin Geng. Variational Continuous Label
Distribution Learning for Multi-Label Text Classification. IEEE Transactions on Knowledge and
Data Engineering (TKDE), 2024, 36(6): 2716-2729.</p>
</li>
<li>
<p>Yuexuan An, Hui Xue, <strong>Xingyu Zhao</strong>, Jing Wang. From Instance to Metric
Calibration: A Unified Framework for Open-World Few-Shot Learning. IEEE Transactions on Pattern
Analysis and Machine Intelligence (TPAMI), 2023, 45(8): 9757-9773.</p>
</li>
<li><p><strong>Xingyu Zhao</strong>, Yuexuan An, Ning Xu, Xin Geng. Continuous Label Distribution
Learning. Pattern Recognition (PRJ), 2023, 133: 109056.</p></li>
<li><p>Nan Zhang, Shifei Ding, Jian Zhang, <strong>Xingyu Zhao</strong>. Robust Spike-and-Slab Deep
Boltzmann Machines for Face Denoising. Neural Computing and Applications (NCAA), 2020, 32(7):
2815-2827.</p></li>
<li><p>Shifei Ding, <strong>Xingyu Zhao</strong>, Xinzheng Xu, Tongfeng Sun, Weikuan Jia. An Effective
Asynchronous Framework for Small Scale Reinforcement Learning Problems. Applied Intelligence
(APIN), 2019, 49(12): 4303-4318.</p></li>
<li><p>Shifei Ding, Wei Du, <strong>Xingyu Zhao</strong>, Lijuan Wang, Weikuan Jia. A New Asynchronous
Reinforcement Learning Algorithm Based on Improved Parallel PSO. Applied Intelligence (APIN), 2019,
49(12): 4211-4222.</p></li>
<li><p>张楠, 丁世飞, 张健, <strong>赵星宇</strong>. 基于噪声数据与干净数据的深度置信网络. 软件学报, 2019, 30(11):3326-3339.</p></li>
<li><p>Shifei Ding, Peng Du, <strong>Xingyu Zhao</strong>, Qiangbo Zhu, Yu Xue. BEMD Image Fusion Based
on PCNN and Compressed Sensing. Soft Computing (SOCO), 2019, 23(20): 10045-10054.</p></li>
<li><p>卞维新, 丁世飞, 张楠, 张健, <strong>赵星宇</strong>. 结合方向高斯带通滤波和深度玻尔兹曼机重构的指纹增强. 软件学报, 2019, 30(6): 1886-1900.
</p></li>
<li><p><strong>Xingyu Zhao</strong>, Shifei Ding, Yuexuan An, Weikuan Jia. Applications of Asynchronous
Deep Reinforcement Learning Based on Dynamic Updating Weights. Applied Intelligence (APIN),
2019, 49(2): 581-591.</p></li>
<li><p>Shifei Ding, <strong>Xingyu Zhao</strong>, Jian Zhang, Xiekai Zhang, Yu Xue. A Review on
Multi-Class TWSVM. Artificial Intelligence Review, 2019, 52(2): 775-801.</p></li>
<li><p><strong>Xingyu Zhao</strong>, Shifei Ding, Yuexuan An, Weikuan Jia. Asynchronous Reinforcement
Learning Algorithms for Solving Discrete Space Path Planning Problems. Applied Intelligence (APIN),
2018, 48(12): 4889-4904.</p></li>
<li><p><strong>赵星宇</strong>, 丁世飞. 深度强化学习研究综述. 计算机科学, 2018, 45(7): 1-6.</p></li>
<li><p>Shifei Ding, <strong>Xingyu Zhao</strong>, Hui Xu, Qiangbo Zhu, Yu Xue. NSCT-PCNN Image Fusion
Based on Image Gradient Motivation. IET Computer Vision (IET-CVI), 2018, 12(4): 377-383.</p></li>
</ul>
<h3>Conference Papers</h3>
<ul>
<li><p><strong>Xingyu Zhao</strong>, Lei Qi, Yuexuan An, Xin Geng. Generalizable Label Distribution
Learning. In: Proceedings of the 31st ACM International Conference on Multimedia (MM'23),
Ottawa, Ontario, Canada, 2023, 8932-8941.</p></li>
<li><p>Yuexuan An, <strong>Xingyu Zhao</strong>, Hui Xue. Learning to Learn from Corrupted Data for
Few-Shot Learning. In: Proceedings of the 32nd International Joint Conference on Artificial
Intelligence (IJCAI'23), Macao, China, 2023, 3423-3431.</p></li>
<li><p><strong>Xingyu Zhao</strong>, Yuexuan An, Ning Xu, Jing Wang, Xin Geng. Imbalanced Label
Distribution Learning. In: Proceedings of the 37th AAAI Conference on Artificial Intelligence
(AAAI'23), Washington, DC, USA, 2023, 11336-11344. (<strong>Oral</strong>)</p></li>
<li><p><strong>Xingyu Zhao</strong>, Yuexuan An, Ning Xu, Xin Geng. Fusion Label Enhancement for
Multi-Label Learning. In: Proceedings of the 31st International Joint Conference on Artificial
Intelligence (IJCAI'22), Vienna, Austria, 2022, 3773-3779. (<strong>Long Oral, Acceptance rate
3.7%</strong>)</p></li>
<li><p>Yuexuan An, Hui Xue, <strong>Xingyu Zhao</strong>, Lu Zhang. Conditional Self-Supervised Learning
for Few-Shot Classification. In: Proceedings of the 30th International Joint Conference on
Artificial Intelligence (IJCAI'21), Montreal, Quebec, Canada, 2021, 2140-2146. </p></li>
<li><p><strong>Xingyu Zhao</strong>, Shifei Ding, Yuexuan An. A New Asynchronous Architecture for
Tabular Reinforcement Learning Algorithms. In: Proceedings of the 8nd International Conference on
Extreme Learning Machines (ELM'17), Yantai, China, 2017, 172-180.
</p></li>
</ul>
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