Searched for: author%3A%22Liem%2C+C.C.S.%22
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Altmeyer, P. (author), Giovan, Angela (author), Buszydlik, Aleksander (author), Dobiczek, Karol (author), van Deursen, A. (author), Liem, C.C.S. (author)
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 goal is to find valid counterfactuals for an individual instance that fulfill various desiderata. The ability of such counterfactuals to handle dynamics like data and...
conference paper 2023
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Liem, C.C.S. (author), Demetriou, A.M. (author)
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 artifacts, in the form of open-access papers, open data, and open-source tools and libraries. In this position paper, we draw attention to another perspective:...
conference paper 2023
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Altmeyer, P. (author), Liem, C.C.S. (author), van Deursen, A. (author)
We present CounterfactualExplanations.jl: a package for generating Counterfactual Explanations (CE) and Algorithmic Recourse (AR) for black-box models in Julia. CE explain how inputs into a model need to change to yield specific model predictions. Explanations that involve realistic and actionable changes can be used to provide AR: a set of...
conference paper 2023
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Bartlett, A.J. (author), Liem, C.C.S. (author), Panichella, A. (author)
Deep learning (DL) models are known to be highly accurate, yet vulnerable to adversarial examples. While earlier research focused on generating adversarial examples using whitebox strategies, later research focused on black-box strategies, as models often are not accessible to external attackers. Prior studies showed that black-box approaches...
conference paper 2023
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Samiotis, I.P. (author), Lofi, C. (author), Alaka, Shaad (author), Liem, C.C.S. (author), Bozzon, A. (author)
In this demo we present Scriptoria, an online crowdsourcing system to tackle the complex transcription process of classical orchestral scores. The system’s requirements are based on experts’ feedback from classical orchestra members. The architecture enables an end- to-end transcription process (from PDF to MEI) using a scalable microtask design...
conference paper 2022
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Huang, H. (author), Liem, C.C.S. (author)
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 design process, which lead to socially exclusive decisions and policies. Faced with similar challenges in dealing with an increasingly diversified audience, the...
conference paper 2022
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Kim, Jaehun (author), Liem, C.C.S. (author)
In the previous decade, Deep Learning (DL) has proven to be one of the most effective machine learning methods to tackle a wide range of Music Information Retrieval (MIR) tasks. It offers highly expressive learning capacity that can fit any music representation needed for MIR-relevant downstream tasks. However, it has been criticized for...
conference paper 2022
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Panichella, A. (author), Liem, C.C.S. (author)
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 been extended to machine learning (ML) systems, and deep learning (DL) in particular; researchers have proposed approaches, tools, and statistically sound heuristics to...
conference paper 2021
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Yildiz, B. (author), Hung, H.S. (author), Krijthe, J.H. (author), Liem, C.C.S. (author), Loog, M. (author), Migut, M.A. (author), Oliehoek, F.A. (author), Panichella, A. (author), Pawełczak, Przemysław (author), Picek, S. (author), de Weerdt, M.M. (author), van Gemert, J.C. (author)
We present ReproducedPapers.org : an open online repository for teaching and structuring machine learning reproducibility. We evaluate doing a reproduction project among students and the added value of an online reproduction repository among AI researchers. We use anonymous self-assessment surveys and obtained 144 responses. Results suggest...
conference paper 2021
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Liem, C.C.S. (author), Panichella, A. (author)
The rise in popularity of machine learning (ML), and deep learning in particular, has both led to optimism about achievements of artificial intelligence, as well as concerns about possible weaknesses and vulnerabilities of ML pipelines. Within the software engineering community, this has led to a considerable body of work on ML testing...
conference paper 2020
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Liem, C.C.S. (author), Mostert, C. (author)
Copyright restrictions prevent the widespread sharing of commercial music audio. Therefore, the availability of resharable pre-computed music audio features has become critical. In line with this, the AcousticBrainz platform<br/>offers a dynamically growing, open and community-contributed large-scale resource of locally computed low-level and...
conference paper 2020
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Samiotis, I.P. (author), Qiu, S. (author), Mauri, A. (author), Liem, C.C.S. (author), Lofi, C. (author), Bozzon, A. (author)
Human annotation is still an essential part of modern transcription workflows for digitizing music scores, either as a standalone approach where a single expert annotator transcribes a complete score, or for supporting an automated Optical Music Recognition (OMR) system. Research on human computation has shown the effectiveness of crowdsourcing...
conference paper 2020
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Weigl, David M. (author), Goebl, Werner (author), Hofmann, Alex (author), Crawford, Tim (author), Zubani, Federico (author), Liem, C.C.S. (author), Porter, Alastair (author)
The Web and other digital technologies have democratised music creation, reception, and analysis, putting music in the hands, ears, and minds of billions of users. Music digital libraries typically focus on an essential subset of this deluge - commercial and academic publications, and historical materials - but neglect to incorporate...
conference paper 2020
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Weigl, David M. (author), Goebl, Werner (author), Crawford, Tim (author), Gkiokas, Aggelos (author), Gutierrez, Nicolas F. (author), Porter, Alastair (author), Santos, Patricia (author), Karreman, Casper (author), Vroomen, Ingmar (author), Liem, C.C.S. (author), Sarasúa, Álvaro (author), Van Tilburg, Marcel (author)
The turn toward the digital has opened up previously difficult to access musical materials to wider musicological scholarship. Digital repositories provide access to publicly licensed score images, score encodings, textual resources, audiovisual recordings, and music metadata. While each repository reveals rich information for scholarly...
conference paper 2019
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Manolios, S. (author), Hanjalic, A. (author), Liem, C.C.S. (author)
The feld of recommender systems has a lot to gain from the feld of psychology. Indeed, many psychology researchers have investigated relations between models that describe humans and consumption preferences. One example of this is personality, which has been shown to be a valid construct to describe people. As a consequence, personality-based...
conference paper 2019
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Kim, Jaehun (author), Manolios, S. (author), Demetriou, A.M. (author), Liem, C.C.S. (author)
Prior research from the field of music psychology has suggested that there are factors common to music preference beyond individual genres. Specifically, research has shown that self-reported ratings of preference for individual musical genres can be reduced to 4 or 5 dimensions, which in turn have been shown to correlate to relevant...
conference paper 2019
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Abderrazik, Hiba (author), Angela, Giovan (author), Brouwer, Hans (author), Janse, Henky (author), Lutz, Sterre (author), Smitskamp, Gwennan (author), Manolios, S. (author), Liem, C.C.S. (author)
Music is often both personally and affectively meaningful to human listeners. However, little work has been done to create music recommender systems that take this into account. In this demo proposal, we present Spotivibes: a first prototype for a new color-based tagging and music recommender system. This innovative tagging system is designed...
conference paper 2019
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Rijlaarsdam, Matthijs (author), Scholten, Sebastiaan (author), Liem, C.C.S. (author)
Recommender systems can be useful in group settings, e.g. when choosing a movie to watch with a group. However, while considerable research in group recommendation has been performed, we still lack truly ecological datasets on group recommendations in real life consumption scenarios. Much of the existing work considers hypothetical...
conference paper 2019
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Liem, C.C.S. (author)
Over the past millennia, music has actively been performed and listened to by mankind, thus also playing an important role in establishing sociocultural identities that have evolved over time. In parallel, for many centuries, newspapers played an important role in informing society on a regular and frequent basis on topics noteworthy at that...
conference paper 2018
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Kim, Jaehun (author), Won, Minz (author), Serra, Xavier (author), Liem, C.C.S. (author)
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 noisy, while certain artists may relate more strongly to certain genres. At the same time, at prediction time, it is not guaranteed that artist labels are available for a...
conference paper 2018
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