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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
</article> </div>Blog Post number 3
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
</article> </div>Blog Post number 2
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
</article> </div>Blog Post number 1
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
</article> </div>portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
Adjacency Constraint for Efficient Hierarchical Reinforcement Learning
Published in IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), April 01, 2023
Authors: Tianren Zhang*, Shangqi Guo*†, Tian Tan, Xiaolin Hu and Feng Chen†
Summary: We proposes an adjacency constraint for goal-conditioned hierarchical reinforcement learning that restricts high-level actions to a k-step adjacent region, theoretically preserving optimality in deterministic MDPs and improving training efficiency in stochastic MDPs, leading to significant performance gains in simulated robotics tasks.
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</article> </div>Paper Title Number 4
Published in GitHub Journal of Bugs, 2024
This paper is about fixing template issue #693.
Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
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Spiking Variational Policy Gradient for Brain Inspired Reinforcement Learning
Published in IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), March 1, 2025
Authors: Zhile Yang, Shangqi Guo†, Ying Fang, Zhaofei Yu and Jian K. Liu
Summary: We design a recurrent winner-take-all network and propose the spiking variational policy gradient (SVPG), a new R-STDP learning method derived theoretically from the global policy gradient.
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</article> </div>talks
Talk 1 on Relevant Topic in Your Field
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This is a description of your talk, which is a markdown file that can be all markdown-ified like any other post. Yay markdown!
</article> </div>Tutorial 1 on Relevant Topic in Your Field
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</article> </div>Talk 2 on Relevant Topic in Your Field
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</article> </div>Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
</article> </div>teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
</article> </div>Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.
</article> </div>