Searched for: author%3A%22Liem%2C+C.C.S.%22
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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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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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König, Cornelius J. (author), Demetriou, A.M. (author), Glock, Philipp (author), Hiemstra, Annemarie M. F. (author), Iliescu, Dragos (author), Ionescu, Camelia (author), Langer, Markus (author), Liem, C.C.S. (author), Linnenbürger, Anja (author)
This article is based on conversations from the project “Big Data in Psychological Assessment” (BDPA) funded by the European Union, which was initiated because of the advances in data science and artificial intelligence that offer tremendous opportunities for personnel assessment practice in handling and interpreting this kind of data. We argue...
journal article 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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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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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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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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Hiemstra, Annemarie M.F. (author), Cassel, Tatjana (author), Born, Marise Ph (author), Liem, C.C.S. (author)
In this article, we describe the implementation of algorithms based on machine learning for personnel selection procedures and how this data-driven approach corresponds to and differentiates from classical psychological assessment. We discuss if, and in what way, bias and discrimination occur when using algorithms based on machine learning...
journal article 2020
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Escalante, Hugo Jair (author), Kaya, Heysem (author), Ali Salah, Albert (author), Escalera, Sergio (author), Güç;lütürk, Yağmur (author), Güçlü, Umut (author), Baro, Xavier (author), Sukma Wicaksana, Achmadnoer (author), Liem, C.C.S. (author)
Explainability and interpretability are two critical aspects of decision support systems. Despite their importance, it is only recently that researchers are starting to explore these aspects. This paper provides an introduction to explainability and interpretability in the context of apparent personality recognition. To the best of our...
journal article 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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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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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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Kim, Jaehun (author), Urbano, Julián (author), Liem, C.C.S. (author), Hanjalic, A. (author)
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 Music Information Retrieval. In order to benefit from deep learning in an effective, but also efficient manner, deep transfer learning has become a common approach...
journal article 2019
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Duan, Zhiyao (author), Essid, Slim (author), Liem, C.C.S. (author), Richard, Gael (author)
In the physical sciences and engineering domains, music has traditionally been considered an acoustic phenomenon. From a perceptual viewpoint, music is naturally associated with hearing, i.e., the audio modality. Moreover, for a long time, the majority of music recordings were distributed through audio-only media, such as vinyl records,...
journal article 2019
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Kim, Jaehun (author), Urbano, Julián (author), Liem, C.C.S. (author), Hanjalic, A. (author)
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 learning solutions employing deep representations frequently have been reported to greatly outperform those using hand-crafted feature representations. At the same time,...
journal article 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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Charisi, Vicky (author), Liem, C.C.S. (author), Gómez, Emilia (author)
Humans have the capacity to invent novel ideas and to create new artifacts that affect the surrounding environment. However, it is unclear how this capacity emerges and develops in biological systems. This paper presents an empirical study which investigates the development of novelty-based cognitive processes in the context of unstructured...
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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