Skeletal and cardiac muscles are remarkable biological machines that support and move our bodies and power the rhythmic work of our lungs and hearts. As well as producing active contractile force, muscles are also passively elastic, which is essential to their performance. The origins of both active contractile and passive elastic forces can be traced to the individual proteins that make up the...

Recently, there are lots of literature on improving the robustness SVM by constructing nonconvex functions, but they seldom theoretically study robust property constructed functions. In this paper, based our recent work, we present a novel capped asymmetric elastic net (CaEN) loss and equip it with as CaENSVM. We derive influence function estimators CaENSVM to explain proposed method. Our resul...

The usage of the package is illustrated for three classification algorithms: pamr (Prediction analysis for Microarrays, [3], implementation in pamr -Rpackage), rf boruta (Random forests with the Boruta algorithm for feature selection, [2], implementation in Boruta-R-package) and scad (Support Vector Machines with Smoothly Clipped Absolute Deviation feature selection, [4], implementation in the ...

Membrane protein prediction is a significant classification problem, requiring the integration of data derived from different sources such as protein sequences, gene expression, protein interactions etc. A generalized probabilistic approach for combining different data sources via supervised selective kernel fusion was proposed in our previous papers. It includes, as particular cases, SVM, Lass...

In the context of the highly increasing number of features that are available nowadays we design a robust and fast method for feature selection. The method tries to select the most representative features that are independent from each other, but are strong together. We propose an algorithm that requires very limited labeled data (as few as one labeled frame per class) and can accommodate as ma...

This project examines methods for predicting the degree to which various drugs inhibit the growth of a range of cancer cell types. Data consist of over 40,000 features for each of 432 cell lines and cell growth inhibition measurements for 24 drugs. The high dimensionality of this data raises challenges that are addressed through Elastic Net parameter tuning. We also investigate Principal Compon...