基本信息
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职业迁徙
个人简介
My research interests are primarily in machine learning and continuous optimization. I am particularly interested in designing robust, tuning-free algorithms for stochastic optimization with applications to fitting neural networks. Such algorithms should be fast and practical, while still possessing rigorous convergence guarantees. This balancing act combines theory and practice and makes optimization for machine learning a very fun space in which to work.
I am also interested in optimization-based methods for scalable Bayesian inference, such as variational inference. Gaussian processes were my first introduction to "real" machine learning and I still find this model class fascinating.
研究兴趣
论文共 11 篇作者统计合作学者相似作者
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arxiv(2024)
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arxiv(2024)
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CoRR (2023): 24888-24924
Amrutha Varshini Ramesh,Aaron Mishkin,Mark Schmidt, Yihan Zhou,Jonathan Wilder Lavington, Jennifer She
CoRR (2023)
Sharan Vaswani, Reza Babenzhad, SAIT AI LAB, MONTREAL,Jose Gallego,Aaron Mishkin, Simon Lacoste-Julien,Nicolas Le Roux
semanticscholar(2020)
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ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019) (2019): 3727-3740
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D-Core
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