1. A Compact Representation of Multiscale Dissimilarity Data by Prototype Selection

    Plasencia-Calaña, Y., Li, Y., Duin, R. P. W., Orozco-Alzate, M., Loog, M. & García-Reyes, E., 2017, Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 21st Iberoamerican Congress, CIARP 2016, Proceedings. Beltrán-Castañón, C., Nyström, I. & Famili, F. (eds.). Cham: Springer, p. 150-157 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10125 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  2. A Game-Theoretic Probabilistic Approach for Detecting Conversational Groups

    Vascon, S., Zemene Mequanint, E., Cristani, M., Hung, HS., Pelillo, M. & Murino, V., 2015, Proceedings of the 12th Asian Conference on Computer Vision. Cremers, D., Reid, I., Saito, H. & Yang, MH. (eds.). Dordrecht: Springer, p. 658-675 18 p. (Lecture Notes in Computer Science; vol. 9007).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  3. A Hierarchical Approach for Associating Body-Worn Sensors to Video Regions in Crowded Mingling Scenarios

    Cabrera Quiros, L. & Hung, H., 2019, In : IEEE Transactions on Multimedia. 21, 7, p. 1867-1879 13 p.

    Research output: Contribution to journalArticleScientificpeer-review

  4. A Large-Scale Study of Agents Learning from Human Reward

    Li, G., Hung, HS. & Whiteson, S., 2015, p. 1-2. 2 p.

    Research output: Contribution to conferenceAbstractScientific

  5. A behavioral investigation of dimensionality reduction

    Lewis, JM., van der Maaten, LJP. & de Sa, VR., 2012, Proceedings of the 34th Annual Conference of the Cognitive Science Society. SN (ed.). Austin, TX, USA: Cognitive Science Society, p. 671-676 6 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  6. A benchmark and comparison of active learning for logistic regression

    Yang, Y. & Loog, M., 2018, In : Pattern Recognition. 83, p. 401-415 15 p.

    Research output: Contribution to journalArticleScientificpeer-review

  7. A data-driven interactome of synergistic genes improves network-based cancer outcome prediction

    Allahyar, A., Ubels, J. & de Ridder, J., 2019, In : PLoS Computational Biology. 15, 2, p. 1-21 21 p., e1006657.

    Research output: Contribution to journalArticleScientificpeer-review

  8. A dissimilarity-based multiple instance learning approach for protein remote homology detection

    Mensi, A., Bicego, M., Lovato, P., Loog, M. & Tax, D. M. J., 2019, In : Pattern Recognition Letters. 128, p. 231-236 6 p.

    Research output: Contribution to journalArticleScientificpeer-review

  9. A novel and automatic mammographic texture resemblance marker is an independent risk factor for breast cancer

    Nielsen, M., Karemore, G., Loog, M., Raundahl, J., Karssemeijer, N., Otten, JDM., Karsdal, MA., Vachon, CM. & Christiansen, C., 2010, In : Cancer Epidemiology: the international journal of cancer epidemiology, detection and prevention. 35, 4, p. 381-387 7 p.

    Research output: Contribution to journalArticleScientificpeer-review

  10. A patient-specific visualization tool for comprehensive analysis of coronary CTA and perfusion MRI data

    Kirisli, HA., Gupta, V., Kirschbaum, S., Neefjes, L., Geuns, RJ., Mollet, N., Lelieveldt, BPF., Reiber, JHC., van Walsum, T. & Niessen, WJ., 2011, In : Proceedings of SPIE- International Society for Optical Engineering. 7964, p. 1-4 4 p.

    Research output: Contribution to journalConference articleScientificpeer-review

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