This paper considers the monotonic transformation model with an unspecified transformation function and an unknown error function, and gives its monotone rank estimation with length-biased and rightcensored data. The ...This paper considers the monotonic transformation model with an unspecified transformation function and an unknown error function, and gives its monotone rank estimation with length-biased and rightcensored data. The estimator is shown to be√n-consistent and asymptotically normal. Numerical simulation studies reveal good finite sample performance and the estimator is illustrated with the Oscar data set. The variance can be estimated by a resampling method via perturbing the U-statistics objective function repeatedly.展开更多
Some two-function minimax theorems are proved. In these results, the staircase and quantitative-topological conditions of both functions involve strictly monotone transformation and mixing of functional values. Conseq...Some two-function minimax theorems are proved. In these results, the staircase and quantitative-topological conditions of both functions involve strictly monotone transformation and mixing of functional values. Consequently, Lin Quan and Kindler＇s minimax theorems are generalized.展开更多
Two two-function minimax theorems are proved. The concavity-convexity conditions of the two functions involve strictly monotone transformations and mixing of the values of the two functions, and are described by the i...Two two-function minimax theorems are proved. The concavity-convexity conditions of the two functions involve strictly monotone transformations and mixing of the values of the two functions, and are described by the inequalities as upward and weakly downward conditions.展开更多
The human face is a valuable biomarker of aging,but the collection and use of its image raise significant privacy concerns.Here we present an approach for facial data masking that preserves age-related features using ...The human face is a valuable biomarker of aging,but the collection and use of its image raise significant privacy concerns.Here we present an approach for facial data masking that preserves age-related features using coordinate-wise monotonic transformations.We first develop a deep learning model that estimates age directly from non-registered face point clouds with high accuracy and generalizability.We show that the model learns a highly indistinguishable mapping using faces treated with coordinate-wise monotonic transformations,indicating that the relative positioning of facial information is a low-level biomarker of facial aging.Through visual perception tests and computational3D face verification experiments,we demonstrate that transformed faces are significantly more difficult to perceive for human but not for machines,except when only the face shape information is accessible.Our study leads to a facial data protection guideline that has the potential to broaden public access to face datasets with minimized privacy risks.展开更多
基金supported by Graduate Innovation Foundation of Shanghai University of Finance and Economics(Grant No.CXJJ2013-451)Cultivation Foundation of Excellent Doctor Degree Dissertation of Shanghai University of Finance and Economics(Grant No.YBPY201504)+4 种基金Program of Educational Department of Fujian Province(Grant Nos.JA14079 and JA12060)Natural Science Foundation of Fujian Province(Grant Nos.2014J01001 and 2012J01028)National Natural Science Foundation of China(Grant No.71271128)the State Key Program of National Natural Science Foundation of China(Grant No.71331006)National Center for Mathematics and Interdisciplinary Sciences,Key Laboratory of Random Complex Structures and Data Science,Chinese Academy of Sciences and Shanghai First-class Discipline A and Innovative Research Team of Shanghai University of Finance and Economics,Program for Changjiang Scholars Innovative Research Team of Ministry of Education(Grant No.IRT13077)
文摘This paper considers the monotonic transformation model with an unspecified transformation function and an unknown error function, and gives its monotone rank estimation with length-biased and rightcensored data. The estimator is shown to be√n-consistent and asymptotically normal. Numerical simulation studies reveal good finite sample performance and the estimator is illustrated with the Oscar data set. The variance can be estimated by a resampling method via perturbing the U-statistics objective function repeatedly.
文摘Some two-function minimax theorems are proved. In these results, the staircase and quantitative-topological conditions of both functions involve strictly monotone transformation and mixing of functional values. Consequently, Lin Quan and Kindler＇s minimax theorems are generalized.
文摘Two two-function minimax theorems are proved. The concavity-convexity conditions of the two functions involve strictly monotone transformations and mixing of the values of the two functions, and are described by the inequalities as upward and weakly downward conditions.
基金supported by the National Natural Science Foundation of China(92049302,92374207,32088101,32330017)the National Key Research and Development Program of China(2020YFA0804000)。
文摘The human face is a valuable biomarker of aging,but the collection and use of its image raise significant privacy concerns.Here we present an approach for facial data masking that preserves age-related features using coordinate-wise monotonic transformations.We first develop a deep learning model that estimates age directly from non-registered face point clouds with high accuracy and generalizability.We show that the model learns a highly indistinguishable mapping using faces treated with coordinate-wise monotonic transformations,indicating that the relative positioning of facial information is a low-level biomarker of facial aging.Through visual perception tests and computational3D face verification experiments,we demonstrate that transformed faces are significantly more difficult to perceive for human but not for machines,except when only the face shape information is accessible.Our study leads to a facial data protection guideline that has the potential to broaden public access to face datasets with minimized privacy risks.
