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12/15/2020
Learning Aggregation Functions
Learning on sets is increasingly gaining attention in the machine learni...
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06/26/2020
Approximating Euclidean by Imprecise Markov Decision Processes
Euclidean Markov decision processes are a powerful tool for modeling con...
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06/19/2020
A general framework for defining and optimizing robustness
Robustness of neural networks has recently attracted a great amount of i...
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04/23/2020
A Complete Characterization of Projectivity for Statistical Relational Models
A generative probabilistic model for relational data consists of a famil...
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10/26/2018
Learning and Interpreting Multi-Multi-Instance Learning Networks
We introduce an extension of the multi-instance learning problem where e...
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07/02/2018
Inference, Learning, and Population Size: Projectivity for SRL Models
A subtle difference between propositional and relational data is that in...
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02/27/2013
A Logic for Default Reasoning About Probabilities
A logic is defined that allows to express information about statistical ...
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02/06/2013
Relational Bayesian Networks
A new method is developed to represent probabilistic relations on multip...
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01/30/2013
Measure Selection: Notions of Rationality and Representation Independence
We take another look at the general problem of selecting a preferred pro...
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04/15/2012