Statistical Epistemic Logic

We introduce a modal logic for describing statistical knowledge, which we call statistical epistemic logic. We propose a Kripke model dealing with probability distributions and stochastic assignments, and show a stochastic semantics for the logic. To our knowledge, this is the first semantics for modal logic that can express the statistical knowledge dependent on non-deterministic inputs and the statistical significance of observed results. By using statistical epistemic logic, we express a notion of statistical secrecy with a confidence level. We also show that this logic is useful to formalize statistical hypothesis testing and differential privacy in a simple and abstract manner

Towards Logical Specification of Statistical Machine Learning

We introduce a logical approach to formalizing statistical properties of machine learning. Specifically, we propose a formal model for statistical classification based on a Kripke model, and formalize various notions of classification performance, robustness, and fairness of classifiers by using epistemic logic. Then we show some relationships among properties of classifiers and those between classification performance and robustness, which suggests robustness-related properties that have not been formalized in the literature as far as we know. To formalize fairness properties, we define a notion of counterfactual knowledge and show techniques to formalize conditional indistinguishability by using counterfactual epistemic operators. As far as we know, this is the first work that uses logical formulas to express statistical properties of machine learning, and that provides epistemic (resp. counterfactually epistemic) views on robustness (resp. fairness) of classifiers.Comment: SEFM'19 conference paper (full version with errors corrected

The sound effect: a study in radical sound design

This research project combines a theoretical intervention into sound ontology, with an empirical investigation into listening experience, in parallel with two technologically focused, research-led creative practice projects. The design follows an iterative cycle of research and creative practice that integrates theory, practice and empirical approaches. The research makes an initial contribution to the field of sound studies by re-appraising the work of pioneers in the field—Pierre Schaeffer and R. Murray Schafer—in light of the concept of the sonic effect. This concept is developed as an effective tool for both sound studies and sound design. This theoretical work attempts to critically and creatively examine the ontology or mode of existence of sonic phenomena and is informed by the post-structural theory of the effect. The theory of the sonic effect is empirically investigated by examining verbal accounts of listening experience elicited by semi-structured interview. Finally, having deconstructed sonic phenomena in terms of their potential to be actualised in diverse contexts, sonic effects are interrogated as a creative strategy in the field of sound design for performance and installed sonic art. Two projects are documented. One is a hybrid live performance installation utilising a novel software design for sound composition and projection. The other is a sound installation work demonstrating a novel loudspeaker design for the creation of very dense sound fields. In this context, design occurs as an effect at the intersection of new technologies of sound production and the production of audible sense. This approach enacts a radical pragmatism that underlies the radical sound design strategy outlined in the thesis