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Tomi Peltola
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2020 – today
- 2020
- [j3]Homayun Afrabandpey, Tomi Peltola, Juho Piironen, Aki Vehtari, Samuel Kaski:
A decision-theoretic approach for model interpretability in Bayesian framework. Mach. Learn. 109(9-10): 1855-1876 (2020)
2010 – 2019
- 2019
- [c9]Homayun Afrabandpey, Tomi Peltola, Samuel Kaski:
Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets. IJCAI 2019: 1959-1966 - [c8]Tomi Peltola, Mustafa Mert Çelikok, Pedram Daee, Samuel Kaski:
Machine Teaching of Active Sequential Learners. NeurIPS 2019: 11202-11213 - [i11]Homayun Afrabandpey, Tomi Peltola, Samuel Kaski:
Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets. CoRR abs/1902.09834 (2019) - [i10]Homayun Afrabandpey, Tomi Peltola, Juho Piironen, Aki Vehtari, Samuel Kaski:
Making Bayesian Predictive Models Interpretable: A Decision Theoretic Approach. CoRR abs/1910.09358 (2019) - [i9]Tomi Peltola, Jussi Jokinen, Samuel Kaski:
Probabilistic Formulation of the Take The Best Heuristic. CoRR abs/1911.00572 (2019) - [i8]Mustafa Mert Çelikok, Tomi Peltola, Pedram Daee, Samuel Kaski:
Interactive AI with a Theory of Mind. CoRR abs/1912.05284 (2019) - 2018
- [j2]Iiris Sundin, Tomi Peltola, Luana Micallef, Homayun Afrabandpey, Marta Soare, Muntasir Mamun Majumder, Pedram Daee, Chen He, Baris Serim, Aki S. Havulinna, Caroline Heckman, Giulio Jacucci, Pekka Marttinen, Samuel Kaski:
Improving genomics-based predictions for precision medicine through active elicitation of expert knowledge. Bioinform. 34(13): i395-i403 (2018) - [c7]Tomi Peltola, Jussi Jokinen, Samuel Kaski:
Probabilistic Formulation of the Take The Best Heuristic. CogSci 2018 - [c6]Pedram Daee, Tomi Peltola, Aki Vehtari, Samuel Kaski:
User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction. IUI 2018: 305-310 - [i7]Tomi Peltola, Mustafa Mert Çelikok, Pedram Daee, Samuel Kaski:
Modelling User's Theory of AI's Mind in Interactive Intelligent Systems. CoRR abs/1809.02869 (2018) - [i6]Tomi Peltola:
Local Interpretable Model-agnostic Explanations of Bayesian Predictive Models via Kullback-Leibler Projections. CoRR abs/1810.02678 (2018) - 2017
- [j1]Pedram Daee, Tomi Peltola, Marta Soare, Samuel Kaski:
Knowledge elicitation via sequential probabilistic inference for high-dimensional prediction. Mach. Learn. 106(9-10): 1599-1620 (2017) - [c5]Luana Micallef, Iiris Sundin, Pekka Marttinen, Muhammad Ammad-ud-din, Tomi Peltola, Marta Soare, Giulio Jacucci, Samuel Kaski:
Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets. IUI 2017: 547-552 - [c4]Pedram Daee, Tomi Peltola, Marta Soare, Samuel Kaski:
Probabilistic Expert Knowledge Elicitation of Feature Relevances in Sparse Linear Regression. IAL@PKDD/ECML 2017: 64-66 - [c3]Homayun Afrabandpey, Tomi Peltola, Samuel Kaski:
Interactive Prior Elicitation of Feature Similarities for Small Sample Size Prediction. UMAP 2017: 265-269 - [i5]Iiris Sundin, Tomi Peltola, Muntasir Mamun Majumder, Pedram Daee, Marta Soare, Homayun Afrabandpey, Caroline Heckman, Samuel Kaski, Pekka Marttinen:
Improving drug sensitivity predictions in precision medicine through active expert knowledge elicitation. CoRR abs/1705.03290 (2017) - [i4]Pedram Daee, Tomi Peltola, Aki Vehtari, Samuel Kaski:
User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction. CoRR abs/1710.04881 (2017) - 2016
- [i3]Luana Micallef, Iiris Sundin, Pekka Marttinen, Muhammad Ammad-ud-din, Tomi Peltola, Marta Soare, Giulio Jacucci, Samuel Kaski:
Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets. CoRR abs/1612.02487 (2016) - [i2]Homayun Afrabandpey, Tomi Peltola, Samuel Kaski:
Interactive Prior Elicitation of Features Similarities for Small Sample Size Prediction. CoRR abs/1612.02802 (2016) - [i1]Pedram Daee, Tomi Peltola, Marta Soare, Samuel Kaski:
Knowledge Elicitation via Sequential Probabilistic Inference for High-Dimensional Prediction. CoRR abs/1612.03328 (2016) - 2014
- [c2]Tomi Peltola, Pasi Jylänki, Aki Vehtari:
Expectation Propagation for Likelihoods Depending on an Inner Product of Two Multivariate Random Variables. AISTATS 2014: 769-777 - [c1]Tomi Peltola, Aki S. Havulinna, Veikko Salomaa, Aki Vehtari:
Hierarchical Bayesian Survival Analysis and Projective Covariate Selection in Cardiovascular Event Risk Prediction. BMA@UAI 2014: 79-88
Coauthor Index
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