基本信息
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职业迁徙
个人简介
Since July 2019, I have been a software engineer at Aurora Innovation, where I am solving perception problems for self-driving cars.
Prior to joining Aurora, I received my Ph.D. from the Machine Learning Department at Carnegie Mellon University (CMU), where I was co-advised by J. Andrew Bagnell and Martial Hebert. My research interest is in cost-effective predictions. Specifically, my Ph.D. thesis is on anytime predictors, which can be interrupted at anytime during inference and still produce valid predictions. Furthermore, the more computational cost is consumed before the interruption, the better the predictions are. Hence, anytime predictors can automatically adjust to and utilize any varying test-time budget limits.
Prior to joining Aurora, I received my Ph.D. from the Machine Learning Department at Carnegie Mellon University (CMU), where I was co-advised by J. Andrew Bagnell and Martial Hebert. My research interest is in cost-effective predictions. Specifically, my Ph.D. thesis is on anytime predictors, which can be interrupted at anytime during inference and still produce valid predictions. Furthermore, the more computational cost is consumed before the interruption, the better the predictions are. Hence, anytime predictors can automatically adjust to and utilize any varying test-time budget limits.
研究兴趣
论文共 10 篇作者统计合作学者相似作者
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ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019) (2019): 10122-10131
引用42浏览0EI引用
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2nd Workshop on Meta-Learning at NeurIPS (2018)
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UAI'16: Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence (2016): 279-288
引用3浏览0EI引用
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semanticscholar(2014)
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