We provide a novel notion of what it means to be interpretable, looking past the usual association with human understanding. Our key insight is that interpretability is not an absolute concept and so we define it relative to a target model, which may or may not be a human. We define a framework that allows for comparing interpretable procedures by linking it to important practical aspects such ...

We examined underaccommodation in hospital medical charts, with a focus on interpretability. In Study 1 147 hospital doctors completed a questionnaire including interpretations of chart entries from their own or another specialty. Study 2 used interviews with 10 doctors to explore interpretations of the same charts and perceptions of the writers. Results indicated that participants interpreted ...

A construction is presented for generating sentences that satisfy a recursively enumerable set of interpretability properties. This construction is then used to prove three previously announced results concerning the lattice of local interpretability types of theories (also known as the Lattice of Chapters). The purpose of this paper is to prove three theorems originally announced without proof...

The provability logic of a theory T is the set of modal formulas, which under any arithmetical realization are provable in T . We slightly modify this notion by requiring the arithmetical realizations to come from a specified set Γ. We make an analogous modification for interpretability logics. We first studied provability logics with restricted realizations, and show that for various natural c...

Granular Computing is an emerging conceptual and computational paradigm for information processing, which concerns representation and processing of complex information entities called “information granules” arising from processes of data abstraction and knowledge derivation. Within Granular Computing, a prominent position is assumed by the “Theory of Fuzzy Information Granulation” (TFIG) whose ...

Importance prioritised coding is a principle aimed at improving the interpretability (or image content recognition) versus bit-rate performance of image coding systems. This can be achieved by (1) detecting and tracking image content or regions of interest (ROI) that are crucial to the interpretation of an image, and (2) compressing them in such a manner that enables ROIs to be encoded with hig...

The goal of this thesis is to modify projection pursuit by trading accuracy for interpretability. The modification produces a more parsimonious and understandable model without sacrificing the structure which projection pursuit seeks. The method retains the nonlinear versatility of projection pursuit while clarifying the results. Following an introduction which outlines the dissertation, the fi...

Dense word embeddings, which encode semantic meanings of words to low dimensional vector spaces, have become very popular in natural language processing (NLP) research due to their state-of-the-art performances in many NLP tasks. Word embeddings are substantially successful in capturing semantic relations among words, so a meaningful semantic structure must be present in the respective vector s...