18 citations · 43 across the 7 of their papers we have counts for
8 papers
Feasible and Desirable Counterfactual Generation by Preserving Human Defined Constraints
Homayun Afrabandpey, Michael Spranger
We present a human-in-the-loop approach to generate counterfactual (CF) explanations that preserve global and local feasibility constraints. Global feasibility constraints refer to…
A Decision-Theoretic Approach for Model Interpretability in Bayesian Framework
Homayun Afrabandpey, Tomi Peltola, Juho Piironen +2
A salient approach to interpretable machine learning is to restrict modeling to simple models. In the Bayesian framework, this can be pursued by restricting the model structure and…
Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets
Homayun Afrabandpey, Tomi Peltola, Samuel Kaski
Learning predictive models from small high-dimensional data sets is a key problem in high-dimensional statistics. Expert knowledge elicitation can help, and a strong line of work f…
Improving drug sensitivity predictions in precision medicine through active expert knowledge elicitation
Iiris Sundin, Tomi Peltola, Muntasir Mamun Majumder +6
Predicting the efficacy of a drug for a given individual, using high-dimensional genomic measurements, is at the core of precision medicine. However, identifying features on which…
An EM Based Probabilistic Two-Dimensional CCA with Application to Face Recognition
Mehran Safayani, Seyed Hashem Ahmadi, Homayun Afrabandpey +1
Recently, two-dimensional canonical correlation analysis (2DCCA) has been successfully applied for image feature extraction. The method instead of concatenating the columns of the…
Interactive Prior Elicitation of Feature Similarities for Small Sample Size Prediction
Homayun Afrabandpey, Tomi Peltola, Samuel Kaski
Regression under the "small , large " conditions, of small sample size and large number of features in the learning data set, is a recurring setting in which learning…
Visualizations Relevant to The User By Multi-View Latent Variable Factorization
Seppo Virtanen, Homayun Afrabandpey, Samuel Kaski
A main goal of data visualization is to find, from among all the available alternatives, mappings to the 2D/3D display which are relevant to the user. Assuming user interaction dat…
Fuzzy Least Squares Twin Support Vector Machines
Javad Salimi Sartakhti, Homayun Afrabandpey, Nasser Ghadiri
Least Squares Twin Support Vector Machine (LST-SVM) has been shown to be an efficient and fast algorithm for binary classification. It combines the operating principles of Least Sq…