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Slokom, M. (author), de Wolf, Peter Paul (author), Larson, M.A. (author)We investigate an attack on a machine learning classifier that predicts the propensity of a person or household to move (i.e., relocate) in the next two years. The attack assumes that the classifier has been made publically available and that the attacker has access to information about a certain number of target individuals. That attacker...conference paper 2022
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Garofalo, Giuseppe (author), Slokom, M. (author), Preuveneers, Davy (author), Joosen, Wouter (author), Larson, M.A. (author)We explore how data modification can enhance privacy by examining the connection between data modification and machine learning. Specifically, machine learning “meets” data modification in two ways. First, data modification can protect the data that is used to train machine learning models focusing it on the intended use and inhibiting...book chapter 2022
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Hung, H.S. (author), Gurrin, Cathal (author), Larson, M.A. (author), Gunes, Hatice (author), Ringeval, Fabien (author), Andre, Elisabeth (author), Morency, Louis-Philippe (author)The rising popularity of Artificial Intelligence (AI) has brought considerable public interest as well faster and more direct transfer of research ideas into practice. One of the aspects of AI that still trails behind considerably is the role of machines in interpreting, enhancing, modeling, generating, and influencing social behavior. Such...conference paper 2021
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Slokom, M. (author), Hanjalic, A. (author), Larson, M.A. (author)In this paper, we propose a new privacy solution for the data used to train a recommender system, i.e., the user–item matrix. The user–item matrix contains implicit information, which can be inferred using a classifier, leading to potential privacy violations. Our solution, called Personalized Blurring (PerBlur), is a simple, yet effective,...journal article 2021
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Scharenborg, O.E. (author), van der Gouw, Nikki (author), Larson, M.A. (author), Marchiori, Elena (author)In this paper, we investigate the connection between how people understand speech and how speech is understood by a deep neural network. A naïve, general feed-forward deep neural network was trained for the task of vowel/consonant classification. Subsequently, the representations of the speech signal in the different hidden layers of the DNN...conference paper 2019
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Strucks, Christopher (author), Slokom, M. (author), Larson, M.A. (author)Past research has demonstrated that removing implicit gender information from the user-item matrix does not result in substantial performance losses. Such results point towards promising solutions for protecting users’ privacy without compromising prediction performance, which are of particular interest in multistakeholder environments. Here,...conference paper 2019
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Slokom, M. (author), Larson, M.A. (author), Hanjalic, A. (author)Data science challenges allow companies, and other data holders, to collaborate with the wider research community. In the area of recommender systems, the potential of such challenges to move forward the state of the art is limited due to concerns about releasing user interaction data. This paper investigates the potential of privacy...conference paper 2019
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Larson, M.A. (author), Slokom, M. (author)Hypotargeting for recommender systems (hyporec) is the idea of controlling the number of unique lists of items that a recommender system can recommend to users during a given time period. The main advantage of hyporec is oversight. If a recommender system offers only a finite number of unique lists, then it becomes feasible for a person...conference paper 2019
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Yadati, N.K. (author), Larson, M.A. (author), Liem, C.C.S. (author), Hanjalic, A. (author)In this paper, we focus on event detection over the timeline of a music track. Such technology is motivated by the need for innovative applications such as searching, non-linearaccess and recommendation. Event detection over the timeline requires time-code level labels in order to train machine learning dels. We use timed comments from...journal article 2018
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Scharenborg, O.E. (author), Larson, M.A. (author)Background music in social interaction settings can hinder conversation. Yet, little is known of how specific properties of music impact speech processing. This paper addresses this knowledge gap by investigating the effect of the 1) complexity of the background music, and 2) the presence versus absence of sung lyrics on spoken-word...conference paper 2018
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Li, X. (author), Larson, M.A. (author), Hanjalic, A. (author)We propose an image representation and matching approach that substantially improves visual-based location estimation for images. The main novelty of the approach, called distinctive visual element matching (DVEM), is its use of representations that are specific to the query image whose location is being predicted. These representations are...journal article 2018
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Yang, J. (author), Sun, Zhu (author), Bozzon, A. (author), Zhang, J. (author), Larson, M.A. (author)The "International Workshop on Recommender Systems for Citizens" (CitRec) is focused on a novel type of recommender systems both in terms of ownership and purpose: recommender systems run by citizens and serving society as a whole.conference paper 2017
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Kille, Benjamin (author), Lommatzsch, Andreas (author), Hopfgartner, Frank (author), Larson, M.A. (author), Brodt, Torben (author)The CLEF NewsREEL challenge allows researchers to evaluate news recommendation algorithms both online (NewsREEL Live) and offline (News-REEL Replay). Compared with the previous year NewsREEL challenged participants with a higher volume of messages and new news portals. In the 2017 edition of the CLEF NewsREEL challenge a wide variety of new...conference paper 2017
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Liang, Yu (author), Loni, B. (author), Larson, M.A. (author)In the CLEF NewsREEL 2017 challenge, we build a delegation model based on the contextual bandit algorithm. Our goal is to investigate whether a bandit approach combined with context extracted from the user side, from the item side and from user-item interaction can help choose the appropriate recommender from a recommender algorithm pool for the...conference paper 2017
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Larson, M.A. (author), Zito, Alessandro (author), Loni, B. (author), Cremonesi, Paolo (author)This paper states the case for the principle of minimal necessary data: If two recommender algorithms achieve the same effectiveness, the better algorithm is the one that requires less user data. Applying this principle involves carrying out training data requirements analysis, which we argue should be adopted as best practice for the...conference paper 2017
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Wang, Bo (author), Larson, M.A. (author)In the 2017 MediaEval Retrieving Diverse Social Images task, we (TUD-MMC team) propose a novel method, namely an intent-based approach, for social image search result diversification. The underlying assumption is that the visual appearance of social images is impacted by the underlying photographic act, i.e., why the images were taken. Better...conference paper 2017
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Kille, Benjamin (author), Lommatzsch, Andreas (author), Hopfgartner, Frank (author), Larson, M.A. (author), de Vries, A.P. (author)Recommender System research has evolved to focus on developing algorithms capable of high performance in online systems. This development calls for a new evaluation infrastructure that supports multi-dimensional evaluation of recommender systems. Today’s researchers should analyze algorithms with respect to a variety of aspects including...conference paper 2017
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Demetriou, A.M. (author), Larson, M.A. (author), Liem, C.C.S. (author)Music has been shown to have a profound effect on lis-teners' internal states as evidenced by neuroscience research. Listeners report selecting and listening to music with specific intent, thereby using music as a tool to achieve desired psychological effects within a given context. In light of these observations, we argue that music information...conference paper 2016
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- Chen, Kuan-Ta (author), Alonso, Omar (author), Larson, M.A. (author), King, Irwin (author) journal article 2016
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Hopfgartner, F. (author), Lommatzsch, A. (author), Kille, B. (author), Larson, M.A. (author), Brodt, T. (author), Cremonesi, P. (author), Karatzoglou, A (author)Increasingly, educators make use of learning-by-doing approaches to teach studentsof STEM programmes the skills that they need to become successful incareers in research and development. However, we argue that the technicalchallenges addressed in these programmes are often too limited and thereforedo not support the students in gaining the more...conference paper 2016
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