34 citations · 119 across the 15 of their papers we have counts for
15 papers
Endogenous Macrodynamics in Algorithmic Recourse
Patrick Altmeyer, Giovan Angela, Aleksander Buszydlik +3
Existing work on Counterfactual Explanations (CE) and Algorithmic Recourse (AR) has largely focused on single individuals in a static environment: given some estimated model, the g…
Explaining Black-Box Models through Counterfactuals
Patrick Altmeyer, Arie van Deursen, Cynthia C. S. Liem
We present CounterfactualExplanations.jl: a package for generating Counterfactual Explanations (CE) and Algorithmic Recourse (AR) for black-box models in Julia. CE explain how inpu…
The Biased Journey of MSD_AUDIO.ZIP
Haven Kim, Keunwoo Choi, Mateusz Modrzejewski +1
The equitable distribution of academic data is crucial for ensuring equal research opportunities, and ultimately further progress. Yet, due to the complexity of using the API for a…
Registered Report : Perception of Other's Musical Preferences Based on Their Personal Values
Sandy Manolios, Catholijn M. Jonker, Cynthia C. S. Liem
The present work is part of a research line seeking to uncover the mysteries of what lies behind people's musical preferences in order to provide better music recommendations. More…
Treat societally impactful scientific insights as open-source software artifacts
Cynthia C. S. Liem, Andrew M. Demetriou
So far, the relationship between open science and software engineering expertise has largely focused on the open release of software engineering research insights and reproducible…
Hidden Author Bias in Book Recommendation
Savvina Daniil, Mirjam Cuper, Cynthia C. S. Liem +2
Collaborative filtering algorithms have the advantage of not requiring sensitive user or item information to provide recommendations. However, they still suffer from fairness relat…
Social Inclusion in Curated Contexts: Insights from Museum Practices
Han-Yin Huang, Cynthia C. S. Liem
Artificial intelligence literature suggests that minority and fragile communities in society can be negatively impacted by machine learning algorithms due to inherent biases in the…
What Are We Really Testing in Mutation Testing for Machine Learning? A Critical Reflection
Annibale Panichella, Cynthia C. S. Liem
Mutation testing is a well-established technique for assessing a test suite's quality by injecting artificial faults into production code. In recent years, mutation testing has bee…
Run, Forest, Run? On Randomization and Reproducibility in Predictive Software Engineering
Cynthia C. S. Liem, Annibale Panichella
Machine learning (ML) has been widely used in the literature to automate software engineering tasks. However, ML outcomes may be sensitive to randomization in data sampling mechani…
ReproducedPapers.org: Openly teaching and structuring machine learning reproducibility
Burak Yildiz, Hayley Hung, Jesse H. Krijthe +9
We present ReproducedPapers.org: an open online repository for teaching and structuring machine learning reproducibility. We evaluate doing a reproduction project among students an…
Are Nearby Neighbors Relatives?: Testing Deep Music Embeddings
Jaehun Kim, Julián Urbano, Cynthia C. S. Liem +1
Deep neural networks have frequently been used to directly learn representations useful for a given task from raw input data. In terms of overall performance metrics, machine learn…
Transfer Learning of Artist Group Factors to Musical Genre Classification
Jaehun Kim, Minz Won, Xavier Serra +1
The automated recognition of music genres from audio information is a challenging problem, as genre labels are subjective and noisy. Artist labels are less subjective and less nois…
One Deep Music Representation to Rule Them All? : A comparative analysis of different representation learning strategies
Jaehun Kim, Julián Urbano, Cynthia C. S. Liem +1
Inspired by the success of deploying deep learning in the fields of Computer Vision and Natural Language Processing, this learning paradigm has also found its way into the field of…
Explaining First Impressions: Modeling, Recognizing, and Explaining Apparent Personality from Videos
Hugo Jair Escalante, Heysem Kaya, Albert Ali Salah +14
Explainability and interpretability are two critical aspects of decision support systems. Within computer vision, they are critical in certain tasks related to human behavior analy…
Vision-based Detection of Acoustic Timed Events: a Case Study on Clarinet Note Onsets
A. Bazzica, J. C. van Gemert, C. C. S. Liem +1
Acoustic events often have a visual counterpart. Knowledge of visual information can aid the understanding of complex auditory scenes, even when only a stereo mixdown is available…