Related papers: Proceedings of NIPS 2017 Symposium on Interpretabl…

While the uptake of data-driven approaches for materials science and chemistry is at an exciting, early stage, to realise the true potential of machine learning models for successful scientific discovery, they must have qualities beyond…

In healthcare there is a pursuit for employing interpretable algorithms to assist healthcare professionals in several decision scenarios. Following the Predictive, Descriptive and Relevant (PDR) framework, the definition of interpretable…

This volume contains papers presented at WLPE 2005, 15th International Workshop on Logic-based methods in Programming Environments. The aim of the workshop is to provide an informal meeting for the researchers working on logic-based tools…

This volume contains the proceedings of the Eighth International Symposium on Games, Automata, Logic and Formal Verification (GandALF 2017). The symposium took place in Roma, Italy, from the 20th to the 22nd of September 2017. The GandALF…

Decision-making processes in healthcare can be highly complex and challenging. Machine Learning tools offer significant potential to assist in these processes. However, many current methodologies rely on complex models that are not easily…

This volume constitutes the informal proceedings of the 32nd International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2022), held on 21-23rd September 2022 as a hybrid (blended) meeting, both in-person (at the…

This volume is the proceedings of the 5th International Symposium on New Frontiers in Human-Robot Interaction, held at the AISB Convention 2016, which took place on the 5th and 6th of April 2016, in Sheffield, U.K. Organised by Maha Salem…

With the availability of large databases and recent improvements in deep learning methodology, the performance of AI systems is reaching or even exceeding the human level on an increasing number of complex tasks. Impressive examples of this…

This volume contains the joint post-proceedings of the 2016 edition of the ML Family Workshop and OCaml Users and Developers Workshop, held in Nara, Japan, in affiliation with ICFP 2016.

Modern predictive analytics underpinned by machine learning techniques has become a key enabler to the automation of data-driven decision making. In the context of business process management, predictive analytics has been applied to making…

The workshop "Mining Scientific Papers: Computational Linguistics and Bibliometrics" (CLBib 2015), co-located with the 15th International Society of Scientometrics and Informetrics Conference (ISSI 2015), brought together researchers in…

Still under debate is the question of whether machine learning is capable of going beyond black-box modeling for complex physical systems. We investigate the generalizing and interpretability properties of learning algorithms. To this end,…

Automated Machine Learning-based systems' integration into a wide range of tasks has expanded as a result of their performance and speed. Although there are numerous advantages to employing ML-based systems, if they are not interpretable,…

Objectives: We study interpretable recidivism prediction using machine learning (ML) models and analyze performance in terms of prediction ability, sparsity, and fairness. Unlike previous works, this study trains interpretable models that…

This volume of the EPTCS contains the proceedings of the 15th international workshop on Qualitative Aspects of Programming Languages and Systems, QAPL 2017, held at April 23, 2017 in Uppsala, Sweden as a satellite event of ETAPS 2017, the…

Deep neural networks exhibit remarkable performance, yet their black-box nature limits their utility in fields like healthcare where interpretability is crucial. Existing explainability approaches often sacrifice accuracy and lack…

Integrating Large Language Models (LLMs) into complex software systems enables the generation of human-understandable explanations of opaque AI processes, such as automated task planning. However, the quality and reliability of these…

Data-driven models are central to scientific discovery. In efforts to achieve state-of-the-art model accuracy, researchers are employing increasingly complex machine learning algorithms that often outperform simple regressions in…

This volume presents the proceedings of the 20th International Conference on Knowledge, Information and Creativity Support Systems (KICSS 2025), held in Nagaoka, Japan, on December 3-5, 2025. The conference, organized in cooperation with…

This volume contains the proceedings of the Ninth Workshop on Fixed Points in Computer Science which took place on the September 1st, 2013 in Torino, Italy as a CSL-affiliated workshop. Past workshops have been held in Brno (1998, MFCS/CSL…