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Yat Long Lo
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2020 – today
- 2024
- [c4]Yat Long Lo, Biswa Sengupta, Jakob Nicolaus Foerster, Michael Noukhovitch:
Learning Multi-Agent Communication with Contrastive Learning. ICLR 2024 - [i8]Mohit Shridhar, Yat Long Lo, Stephen James:
Generative Image as Action Models. CoRR abs/2407.07875 (2024) - 2023
- [c3]Yat Long Lo, Christian Schröder de Witt, Samuel Sokota, Jakob Nicolaus Foerster, Shimon Whiteson:
Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning. ICLR 2023 - [i7]Yat Long Lo, Christian Schröder de Witt, Samuel Sokota, Jakob Nicolaus Foerster, Shimon Whiteson:
Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning. CoRR abs/2303.10733 (2023) - [i6]Yat Long Lo, Biswa Sengupta, Jakob N. Foerster, Michael Noukhovitch:
Learning to Communicate using Contrastive Learning. CoRR abs/2307.01403 (2023) - [i5]Jobst Heitzig, Jörg Oechssler, Christoph Pröschel, Niranjana Ragavan, Yat Long Lo:
Improving International Climate Policy via Mutually Conditional Binding Commitments. CoRR abs/2307.14267 (2023) - 2022
- [i4]Yat Long Lo, Biswa Sengupta:
Learning to Ground Decentralized Multi-Agent Communication with Contrastive Learning. CoRR abs/2203.03344 (2022) - 2020
- [c2]Sina Ghiassian, Banafsheh Rafiee, Yat Long Lo, Adam White:
Improving Performance in Reinforcement Learning by Breaking Generalization in Neural Networks. AAMAS 2020: 438-446 - [i3]Sina Ghiassian, Banafsheh Rafiee, Yat Long Lo, Adam White:
Improving Performance in Reinforcement Learning by Breaking Generalization in Neural Networks. CoRR abs/2003.07417 (2020)
2010 – 2019
- 2019
- [j1]Yat Long Lo, Chung Yu Woo, Ka Lok Ng:
The necessary roadblock to artificial general intelligence: corrigibility. AI Matters 5(3): 77-84 (2019) - [i2]Yat Long Lo, Sina Ghiassian:
Overcoming Catastrophic Interference in Online Reinforcement Learning with Dynamic Self-Organizing Maps. CoRR abs/1910.13213 (2019) - 2017
- [c1]Subham De, Shreyans Chowdhary, Aniket Shirke, Yat Long Lo, Robin Kravets
, Hari Sundaram
:
Finding by Counting: A Probabilistic Packet Count Model for Indoor Localization in BLE Environments. WiNTECH 2017: 67-74 - [i1]Subham De, Shreyans Chowdhary, Aniket Shirke, Yat Long Lo, Robin Kravets, Hari Sundaram:
Finding by Counting: A Probabilistic Packet Count Model for Indoor Localization in BLE Environments. CoRR abs/1708.08144 (2017)
Coauthor Index
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last updated on 2024-08-17 23:44 CEST by the dblp team
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