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Accurate estimation of tree biomass is required for accounting for and monitoring forest carbon stocking. Allometric biomass equations constructed by classical statistical methods are widely used to p...
As an important land surface vegetation parameter, fractional vegetation cover (FVC) has been widely used in many Earth system ecological and climate models. In particular, high-quality and reliable F...
Accurate HIV incidence estimation based on individual recent infection status (recent vs long-term infection) is important for monitoring the epidemic, targeting interventions to those at greatest ris...
We propose a sequential method for implementing reconstruction regression. With a space-filling design of a small sample size, we use GP interpolation-based reconstruction regression to build initial ...
The problem of using covariates to predict shapes of objects in a regression setting is important in many fields. A formal statistical approach, termed geodesic regression model, is commonly used for ...
In this paper we present a practical protocol for secure ridge regression. We develop the necessary secure linear algebra tools, using only basic arithmetic over prime fields. In particular, we will s...
In this work, we demonstrate the use the CKKS homomorphic encryption scheme to train a large number of logistic regression models simultaneously, as needed to run a genome-wide association study (GWAS...
Cryptographic libraries often feature multiple implementations of primitives to meet both the security needs of handling private information and the performance requirements of modern services when th...
The sharing of biomedical data is crucial to enable scientific discoveries across institutions and improve health care. For example, genome-wide association studies (GWAS) based on a large number of s...
Background Privacy-preserving computations on genomic data, and more generally on medical data, is a critical path technology for innovative, life-saving research to positively and equally impact the ...
We aimed to evaluate different orders of fixed and random effects in random regression models (RRM) based on Legendre orthogonal polynomials as well as to verify the feasibility of these models to des...
In this digital world, there is a large requirement of high resolution satellite image. Images at a low resolution may contain relevant information that has to be integrated with the high resolution i...
The significant advancements in the field of homomorphic encryption have led to a grown interest in securely outsourcing data and computation for privacy critical applications. In this paper, we focus...
Machine learning on encrypted data is a cryptographic method for analyzing private and/or sensitive data while keeping privacy. In the training phase, it takes as input an encrypted training data and ...
More precisely, given a list of approximately 15001500 patient records, each with 1818 binary features containing information on specific mutations, the idea was for the data holder to encrypt the rec...

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