Machine Learning

Failure State Prediction for Automated Analyzers for Analyzing a Biological Sample
A method for predicting a failure state of an automated analyzer for analyzing a biological sample is disclosed. The method includes …
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Spring 2019: Kernel Methods in Machine Learning
Master course at African Master’s in Machine Intelligence (AMMI).
21 Jan 2019
Spring 2019: Kernel Methods in Machine Learning
The Weighted Kendall and High-order Kernels for Permutations
We propose new positive definite kernels for permutations. First we introduce a weighted version of the Kendall kernel, which allows to …
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The Weighted Kendall and High-order Kernels for Permutations
The Kendall and Mallows Kernels for Permutations
We show that the widely used Kendall tau correlation coefficient, and the related Mallows kernel, are positive definite kernels for …
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The Kendall and Mallows Kernels for Permutations
kernrank
C++ package (with an R interface) implementing kernel methods for rank data
20 Nov 2017
kernrank
kmr
A kernel multitask regression algorithm implemented in R
20 Nov 2017
kmr
Kernel Multitask Regression for Toxicogenetics
The development of high-throughput in vitro assays to study quantitatively the toxicity of chemical compounds on genetically …
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Rank-based Molecular Prognosis and Network-guided Biomarker Discovery for Breast Cancer
Breast cancer is the second most common cancer worldwide and the leading cause of women’s death from cancer. Improving cancer prognosis …
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Controlling the distance to a Kemeny consensus without computing it
Due to its numerous applications, rank aggregation has become a problem of major interest across many fields of the computer science …
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Controlling the distance to a Kemeny consensus without computing it
The Kendall and Mallows Kernels for Permutations
We show that the widely used Kendall tau correlation coefficient is a positive definite kernel for permutations. It offers a …
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The Kendall and Mallows Kernels for Permutations