Zobrazeno 1 - 10
of 553
pro vyhledávání: '"Zhao, Sihai"'
Autor:
Xin, Huqin, Zhao, Sihai Dave
Covariance matrix estimation, a classical statistical topic, poses significant challenges when the sample size is comparable to or smaller than the number of features. In this paper, we frame covariance matrix estimation as a compound decision proble
Externí odkaz:
http://arxiv.org/abs/2406.13876
Wide heterogeneity exists in cancer patients' survival, ranging from a few months to several decades. To accurately predict clinical outcomes, it is vital to build an accurate predictive model that relates patients' molecular profiles with patients'
Externí odkaz:
http://arxiv.org/abs/2310.07187
Autor:
Barbehenn, Alton, Zhao, Sihai Dave
Biomarkers are often measured in bulk to diagnose patients, monitor patient conditions, and research novel drug pathways. The measurement of these biomarkers often suffers from detection limits that result in missing and untrustworthy measurements. F
Externí odkaz:
http://arxiv.org/abs/2306.07239
Autor:
Barbehenn, Alton, Zhao, Sihai Dave
The simultaneous estimation of multiple unknown parameters lies at heart of a broad class of important problems across science and technology. Currently, the state-of-the-art performance in the such problems is achieved by nonparametric empirical Bay
Externí odkaz:
http://arxiv.org/abs/2205.00336
Autor:
Mayers, Jared R., Varon, Jack, Zhou, Ruixuan R., Daniel-Ivad, Martin, Beaulieu, Courtney, Bhosle, Amrisha, Glasser, Nathaniel R., Lichtenauer, Franziska M., Ng, Julie, Vera, Mayra Pinilla, Huttenhower, Curtis, Perrella, Mark A., Clish, Clary B., Zhao, Sihai D., Baron, Rebecca M., Balskus, Emily P.
Publikováno v:
In Cell 25 July 2024 187(15):4095-4112
Publikováno v:
In Ecological Informatics July 2024 81
Autor:
Wei, Panpan, Tian, Kangli, Liu, Haole, Li, Kexin, Alam, Naqash, Cheng, Daxin, Li, Meng, He, Xue, Guo, Jia, Wang, Rong, Wang, Weirong, Bai, Liang, Liu, Enqi, Xu, Baohui, Li, Yankui, Zhao, Sihai
Publikováno v:
In BBA - Molecular Basis of Disease June 2024 1870(5)
Publikováno v:
In Expert Systems With Applications 15 April 2024 240
Autor:
Wang, Yihe, Zhao, Sihai Dave
We propose a new prediction method for multivariate linear regression problems where the number of features is less than the sample size but the number of outcomes is extremely large. Many popular procedures, such as penalized regression procedures,
Externí odkaz:
http://arxiv.org/abs/2104.08970
Capturing patterns of variation present in a dataset is important in exploratory data analysis and unsupervised learning. Contrastive dimension reduction methods, such as contrastive principal component analysis (cPCA), find patterns unique to a targ
Externí odkaz:
http://arxiv.org/abs/2104.08157