5 papers
Scalable Pairwise Kernel Learning with Stochastic Vec Trick
Napsu Karmitsa, Tapio Pahikkala, Antti Airola
Pairwise learning is a specialized form of supervised learning that focuses on predicting outcomes for pairs of objects. In this work, we introduce SPaiK, a new scalable kernel lea…
A Comprehensive Guide to Differential Privacy: From Theory to User Expectations
Napsu Karmitsa, Antti Airola, Tapio Pahikkala +1
The increasing availability of personal data has enabled significant advances in fields such as machine learning, healthcare, and cybersecurity. However, this data abundance also r…
Evaluation metrics for temporal preservation in synthetic longitudinal patient data
Katariina Perkonoja, Parisa Movahedi, Antti Airola +2
This study introduces a set of metrics for evaluating temporal preservation in synthetic longitudinal patient data, defined as artificially generated data that mimic real patients'…
Interaction Concordance Index: Performance Evaluation for Interaction Prediction Methods
Tapio Pahikkala, Riikka Numminen, Parisa Movahedi +2
Consider two sets of entities and their members' mutual affinity values, say drug-target affinities (DTA). Drugs and targets are said to interact in their effects on DTAs if drug's…
Empirical investigation of multi-source cross-validation in clinical ECG classification
Tuija Leinonen, David Wong, Antti Vasankari +4
Traditionally, machine learning-based clinical prediction models have been trained and evaluated on patient data from a single source, such as a hospital. Cross-validation methods…