Human cognition and behavior heavily relies on the notion that evidence (data, premises)
can affect the credibility of hypotheses (theories, conclusions). This general idea seems to …

This paper presents a thorough description of Nyamulagira's January 2010 volcanic
eruption (North Kivu, Democratic Republic of Congo), based on a combination of field …

Statistical learning theory is often associated with the principle of Occam's razor, which
recommends a simplicity preference in inductive inference. This paper distills the core …

In recent years, the question of the reliability of Machine Learning (ML) methods has
acquired significant importance, and the analysis of the associated uncertainties has …

Explaining the connection, if any, between simplicity and truth is among the deepest
problems facing the philosophy of science, statistics, and machine learning. Say that an …

This paper considers the epistemic justification for a simplicity preference in inductive
inference that may be obtained from the machine learning framework of statistical learning …

We defend a set of acceptance rules that avoids the lottery paradox, that is closed under
classical entailment, and that accepts uncertain propositions without ad hoc restrictions. We …

We investigate the issues of inductive problem-solving and learning by doxastic agents. We
provide topological characterizations of solvability and learnability, and we use them to …

We analyze the learning power of iterated belief revision methods, and in particular their
universality: whether or not they can learn everything that can be learnt. We look in particular …

Formal learning theory is the mathematical embodiment of a normative epistemology. It
deals with the question of how an agent should use observations about her environment to …