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Blake Woodworth
Ph.D
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My research is generally in machine learning and optimization. The primary focus of my PhD research has been the theory of optimization, with a particular emphasis on precisely understanding the oracle complexity of convex, non-convex, and distributed optimization problems. In addition to my work in optimization, I have also been interested in efforts to understand modern, highly overparametrized machine learning models through the lens of implicit regularization. Earlier in my PhD, I also enjoyed working on fairness in ML and on adaptive data analysis
Papers23 papers
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Woodworth Blake,Gunasekar Suriya,Lee Jason D., Moroshko Edward,Savarese Pedro, Golan Itay,Soudry Daniel,Srebro Nathan
COLT, pp.3635-3673, (2020)
Cited by36EIBibtex
COLT 2020, (2020)
Bibtex
AISTATS, pp.2830-2840, (2020)
Cited by3EIBibtex
NIPS 2020, (2020)
Cited by3EIBibtex
ICML, pp.10334-10343, (2020)
Cited by38EIBibtex
COLT, pp.3202-3210, (2019)
Cited by1EIBibtex
CoRR, (2019): 2830-2840
Cited by3EIBibtex
COLT, (2019): 1319-1345
Cited by16EIBibtex
COLT, pp.627-647, (2019)
EIBibtex
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), (2019)
Cited by61Bibtex
international conference on machine learning, (2018)
Cited by33EIBibtex
NeurIPS, (2018)
Cited by23EIBibtex
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), (2018): 6531-6540
Cited by2EIBibtex
arXiv: Optimization and Control, (2017)
Cited by14Bibtex
information theory and applications, (2017)
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