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@@ -94,7 +94,7 @@ <h2>Publications (* Equal Contribution, # Corresponding author) &nbsp&nbsp&nbsp<
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 	<li><p><b>Feng Xie</b>, Biwei Huang, Zhengming Chen, Yangbo He, Zhi Geng, and Kun Zhang. <a href="https://proceedings.mlr.press/v162/xie22a.html" target="_blank">Identification of Linear Non-Gaussian Latent Hierarchical Structure</a>. <i>Thirty-ninth International Conference on Machine Learning (ICML)</i>, Baltimore, Maryland USA, 2022. [<a href="https://proceedings.mlr.press/v162/xie22a/xie22a.pdf" target="_blank">pdf</a>][<a href="https://media.icml.cc/Conferences/ICML2022/supplementary/xie22a-supp.zip" target="_blank">code</a>]</p>
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-	<li><p>Biwei Huang*, Charles Low*, <b>Feng Xie</b>, Clark Glymour, Kun Zhang. <a href="https://openreview.net/forum?id=lIeuKiTZsLY" target="_blank">Latent Hierarchical Causal Structure Discovery with Rank Constraints</a>. <i>Advances in Neural Information Processing Systems (NeurIPS)</i>, 2022.</p>
+	<li><p>Biwei Huang, Charles Low, <b>Feng Xie</b>, Clark Glymour, Kun Zhang. <a href="https://openreview.net/forum?id=lIeuKiTZsLY" target="_blank">Latent Hierarchical Causal Structure Discovery with Rank Constraints</a>. <i>Advances in Neural Information Processing Systems (NeurIPS)</i>, 2022.</p>
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 	<li><p>Z. Chen*, <b>Feng Xie*</b>, Jie Qiao*, Zhifeng Hao, Kun Zhang, and Ruichu Cai. <a href="https://ojs.aaai.org/index.php/AAAI/article/view/20585" target="_blank">Identification of Linear Latent Variable Model with Arbitrary Distribution</a>. <i>Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)</i>, Vancouver, CANADA, 2022. [<a href="https://www.aaai.org/AAAI22Papers/AAAI-6434.ChenZ.pdf" target="_blank">pdf</a>]</p>
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@@ -138,7 +138,7 @@ <h2>Publications (* Equal Contribution, # Corresponding author) &nbsp&nbsp&nbsp<
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 <font size="3"><b>Causal Effect Estimation/Policy Learning</b></font> 
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-    <li><p>Peng Wu, Ziyu Shen, <b>Feng Xie</b>, Zhongyao Wang, Chunchen Liu, and Yan Zeng.<a href="https://icml.cc/virtual/2024/poster/34884" target="_blank">Policy Learning for Balancing Short-Term and Long-Term Rewards.</a>. <i>The Forty-first International Conference on Machine Learning (ICML)</i>, Vienna, Austria, 2024. [<a href="https://icml.cc/virtual/2024/poster/34884" target="_blank">pdf</a>]</p>
+    <li><p>Peng Wu, Ziyu Shen, <b>Feng Xie</b>, Zhongyao Wang, Chunchen Liu, and Yan Zeng. <a href="https://icml.cc/virtual/2024/poster/34884" target="_blank">Policy Learning for Balancing Short-Term and Long-Term Rewards.</a>. <i>The Forty-first International Conference on Machine Learning (ICML)</i>, Vienna, Austria, 2024. [<a href="https://icml.cc/virtual/2024/poster/34884" target="_blank">pdf</a>]</p>
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 </ul>