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Mingyuan Zhou(周明远)
Associate Professor
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My research lies at the intersection of Bayesian statistics and machine learning. I am interested in developing statistical theory and methods, hierarchical models, and efficient Bayesian inference for big data. I am currently focused on the development of nonparametric Bayesian hierarchical models for count data analysis, categorical data analysis, mixture modeling (clustering, mixed-membership modeling, topic modeling), dictionary learning (feature learning, factor analysis), network modeling, and deep learning.
Papers130 papers
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ICLR 2021, (2021)
ICLR, (2020)
machine vision applications, no. 6 (2020): 1-11
UAI, pp.540-549, (2020)
EMNLP 2020, pp.485-497, (2020)
NIPS 2020, (2020)
NIPS 2020, (2020)
NIPS 2020, (2020)
ICLR, (2020)
AISTATS, pp.3959-3969, (2020)
IEEE transactions on pattern analysis and machine intelligence, (2020): 1-1
ICCP, pp.1-12, (2020)
ICML, pp.3810-3821, (2020)
Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki,Nick Duffield,Mingyuan Zhou,Krishna Narayanan,Xiaoning Qian
ICML, pp.4094-4104, (2020)
ICLR, (2020)
IEEE Transactions on Pattern Analysis and Machine Intelligence, no. 7 (2020): 1594-1605
AISTATS, pp.3905-3916, (2020)
ICLR, (2020)
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