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It's hard for me to put a finger on what exactly my research interests are; pretty much all things ML interest me, so long as the research is done right. I am a strong refuser of the wrong "publish or perish" mindset, and have no interest in publishing uninspiring work. To me, the upshot of Reinforcement Learning research from the past few years is that RL needs a major overhaul. To this end, during my PhD, I aim to conduct my research on training agents that learn to solve MDPs by directly optimizing for the metrics that we we consider important for a typical RL algorithm, i.e. sample efficiency, safe exploration, etc. I believe recent advances in meta-learning and sequence modeling could potentially help us take the next leap in RL.
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ICLR 2024 (2023)
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