Abstract: Outsourcing logistic regression classification services to the cloud is highly beneficial for streaming data. However, it raises critical privacy concerns for the input data and the training ...
After a demoralizing period punctuated by the withdrawal of one of the few marketed therapies for ALS, investment in new biotechs, state-backed collaborative initiatives and buzz at BIO2025 suggest a ...
Abstract: Rain prediction is challenging due to the complex combination of atmospheric factors. This paper presents the application of logistic regression modelling to predict rainfall the next day, ...
1 Department of Computer Science, Nagoya Institute of Technology, Aichi, Japan 2 RIKEN Center for Advanced Intelligence Project, Tokyo, Japan In recent years, a learning method for classifiers using ...
Background: Sepsis is a life-threatening disease associated with a high mortality rate, emphasizing the need for the exploration of novel models to predict the prognosis of this patient population.
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This article presents a complete demo program for logistic regression, using batch stochastic gradient descent training with weight decay. Compared to other binary classification techniques, logistic ...
Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka565-0871, Japan ...
An illustration of a magnifying glass. An illustration of a magnifying glass.
The fundamental technique has been studied for decades, thus creating a huge amount of information and alternate variations that make it hard to tell what is key vs. non-essential information.
"Welcome to this first use case tutorial, where we are going to show how to use TenSEAL for training and evaluating a logistic regression (LR) model on encrypted data (using homomorphic encryption) ...