1 citations · 1 across the 3 of their papers we have counts for
6 papers
Interactive AI with a Theory of Mind
Mustafa Mert Çelikok, Tomi Peltola, Pedram Daee +1
Understanding each other is the key to success in collaboration. For humans, attributing mental states to others, the theory of mind, provides the crucial advantage. We argue for f…
Probabilistic Formulation of the Take The Best Heuristic
Tomi Peltola, Jussi Jokinen, Samuel Kaski
The framework of cognitively bounded rationality treats problem solving as fundamentally rational, but emphasises that it is constrained by cognitive architecture and the task envi…
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…
Local Interpretable Model-agnostic Explanations of Bayesian Predictive Models via Kullback-Leibler Projections
Tomi Peltola
We introduce a method, KL-LIME, for explaining predictions of Bayesian predictive models by projecting the information in the predictive distribution locally to a simpler, interpre…
Machine Teaching of Active Sequential Learners
Tomi Peltola, Mustafa Mert Çelikok, Pedram Daee +1
Machine teaching addresses the problem of finding the best training data that can guide a learning algorithm to a target model with minimal effort. In conventional settings, a teac…