This is a work in progress research work focusing on localization of structures like lesions and lung capacities on MRI and X-ray images. The project is done in collaboration with the HKU-IRIS laboratory.
This is a personal side project to explore the use of Deep RL in stock trading. As a start, I am currently trying to reproduce the results of the paper - Deep Robust Reinforcement Learning for Practical Algorithmic Trading
This is a depression classifier that attempts to identify suicidal users using their social media updates. It is part of my undergraduate capstone project.
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Published in The 11th Workshop on Wireless Network Testbeds, Experimental evaluation & Characterization, Association for Computing Machinery, 2017
Recommended citation: De, Subham, Shreyans Chowdhary, Aniket Shirke, Yat Long Lo, Robin Kravets, and Hari Sundaram. In Proceedings of the 11th Workshop on Wireless Network Testbeds, Experimental evaluation & Characterization, pp. 67-74. ACM , 2017. https://richielo.github.io/files/BT_WNTECH_WS_17.pdf
Published in MICCAI-19 Workshop on Artificial Intelligence in Radiation Therapy, 2019
Recommended citation: Liu, Zhiyu, Wenhao Jiang, Kit Hang Lee, Yat Long Lo, Yui Lun Ng, Qi Dou, Varut Vardhanabhuti and Ka Wai Kwok. MICCAI Workshop on Artificial Intelligence in Radiation Therapy. 2019 https://richielo.github.io/files/Prostate_NN_MICCAI_WS_19.pdf
Published in NeurIPS-19 Biological and Artificial Reinforcement Learning Workshop, 2019
Recommended citation: Lo, Yat Long and Sina Ghiassian. NeurIPS Workshop on Biological and Artificial Reinforcement Learning . 2019. https://richielo.github.io/files/RL_DSOM_NEURIPS_WS_19.pdf
Published in AI Matters, Special Interest Group on Artificial Intelligence, Association for Computing Machinery, 2019
Recommended citation: Lo, Yat Long, Chung Yu Woo, and Ka Lok Ng. The Necessary Roadblock to Artificial General Intelligence: Corrigibility. AI Matters. 2019. (Winner of 2018 ACM SIGAI Student Essay Contest on Artificial Intelligence Technologies) https://richielo.github.io/files/Corrigibility_AGI_SIGAI_19.pdf
Published in The 19th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS) , 2020
Recommended citation: Ghiassian, Sina, Banafsheh Rafiee, Yat Long Lo, Adam White. In Proceedings of the 19th International Conference on Autonomous Agents and Multi-Agent Systems. AAMAS 2020. https://richielo.github.io/files/RL_BG_NN_AAMAS_20.pdf
Published in ICAPS-20 Workshop on Bridging the Gap Between AI Planning and Reinforcement Learning , 2020
Recommended citation: Lo, Yat Long, Jia Pan and Albert Y.S. Lam. ICAPS Workshop on Bridging the Gap Between AI Planning and Reinforcement Learning. 2020. https://richielo.github.io/files/RL_BDRL_ICAPS_WS_20.pdf
Published in ICLR-22 Emergent Communication Workshop, 2022
Recommended citation: Lo, Yat Long and Biswa Sengupta. ICLR Workshop on Emergent Communication . 2022. (Runner-up Best Paper) https://richielo.github.io/files/MARL_COMM_CACL_ICLR_WS_22.pdf
Published in The 11th International Conference on Learning Representations (ICLR), 2023
Recommended citation: Lo, Yat Long, Christian Schroeder de Witt, Samuel Sokota, Jakob Foerster, Shimon Whiteson. In Proceedings of The 11th International Conference on Learning Representations . ICLR 2023. https://richielo.github.io/files/RL_MARL_CTDU_ICLR_23.pdf
Published in The 11th International Conference on Learning Representations (ICLR), 2024
Recommended citation: Lo, Yat Long, Biswa Sengupta, Jakob Foerster, Michael Noukhovitch. In Proceedings of The 11th International Conference on Learning Representations . ICLR 2024. https://richielo.github.io/files/RL_MARL_CACL_ICLR_24.pdf
Published in In Review, 2024
Recommended citation: Mohit Shridhar*, Lo, Yat Long*, Stephen James. Conference on Robot Learning. 2024. https://richielo.github.io/files/IL_GENIMA_CORL_24.pdf
Published:
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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