20 citations · 24 across the 3 of their papers we have counts for
4 papers
Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets
Luana Micallef, Iiris Sundin, Pekka Marttinen +5
Providing accurate predictions is challenging for machine learning algorithms when the number of features is larger than the number of samples in the data. Prior knowledge can impr…
GFA: Exploratory Analysis of Multiple Data Sources with Group Factor Analysis
Eemeli Leppäaho, Muhammad Ammad-ud-din, Samuel Kaski
The R package GFA provides a full pipeline for factor analysis of multiple data sources that are represented as matrices with co-occurring samples. It allows learning dependencies…
Drug response prediction by inferring pathway-response associations with Kernelized Bayesian Matrix Factorization
Muhammad Ammad-ud-din, Suleiman A. Khan, Disha Malani +4
A key goal of computational personalized medicine is to systematically utilize genomic and other molecular features of samples to predict drug responses for a previously unseen sam…
Regression with n1 by Expert Knowledge Elicitation
Marta Soare, Muhammad Ammad-ud-din, Samuel Kaski
We consider regression under the "extremely small large " condition, where the number of samples is so small compared to the dimensionality that predictors cannot be…