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pro vyhledávání: '"Rho, Saeyoung"'
Synthetic control is a causal inference tool used to estimate the treatment effects of an intervention by creating synthetic counterfactual data. This approach combines measurements from other similar observations (i.e., donor pool ) to predict a cou
Externí odkaz:
http://arxiv.org/abs/2303.14084
Autor:
Tang, Shuai, Aydore, Sergul, Kearns, Michael, Rho, Saeyoung, Roth, Aaron, Wang, Yichen, Wang, Yu-Xiang, Wu, Zhiwei Steven
We revisit the problem of differentially private squared error linear regression. We observe that existing state-of-the-art methods are sensitive to the choice of hyperparameters -- including the ``clipping threshold'' that cannot be set optimally in
Externí odkaz:
http://arxiv.org/abs/2303.03451
Autor:
Rho, Saeyoung.
Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, September, 2020
Thesis: S.M. Massachusetts Institute of Technology, Dep
Thesis: S.M. Massachusetts Institute of Technology, Dep
Externí odkaz:
https://hdl.handle.net/1721.1/129323