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Algorithms with applications in machine learning, radiomics, computer networks and single-cell genomics
Braverman’s research interests include efficient sublinear algorithms (such as sketches and coresets) and their applications to data science, machine and deep learning, systems and networks, physics and astronomy, computational genomics, oncology and radiology. He is a recipient of NSF CAREER award, Google Faculty Award and Cisco Faculty Award.
Algorithms with applications in machine learning, radiomics, computer networks and single-cell genomics
Braverman’s research interests include efficient sublinear algorithms (such as sketches and coresets) and their applications to data science, machine and deep learning, systems and networks, physics and astronomy, computational genomics, oncology and radiology. He is a recipient of NSF CAREER award, Google Faculty Award and Cisco Faculty Award.
研究兴趣
论文共 168 篇作者统计合作学者相似作者
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Andrea Soltoggio,Eseoghene Ben-Iwhiwhu,Vladimir Braverman,Eric Eaton, Benjamin Epstein,Yunhao Ge, Lucy Halperin,Jonathan How,Laurent Itti, Michael A. Jacobs, Pavan Kantharaju, Long Le,
Nature Machine Intelligenceno. 3 (2024): 251-264
Diagnostics (Basel, Switzerland)no. 6 (2024)
Trans. Mach. Learn. Res. (2023)
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PROCEEDINGS OF THE 2023 ACM SIGCOMM 2023 CONFERENCE, SIGCOMM 2023pp.1074-1087, (2023)
CoRR (2023)
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