David Jonathan Miller

    • 1677 Citations
    • 23 h-Index
    1992 …2019
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    Fingerprint Dive into the research topics where David Jonathan Miller is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

    • 2 Similar Profiles
    Classifiers Engineering & Materials Science
    Entropy Engineering & Materials Science
    Labels Engineering & Materials Science
    Vector quantization Engineering & Materials Science
    Annealing Engineering & Materials Science
    Decoding Engineering & Materials Science
    Cluster Analysis Medicine & Life Sciences
    Learning Medicine & Life Sciences

    Network Recent external collaboration on country level. Dive into details by clicking on the dots.

    Research Output 1992 2019

    Asymmetric independence modeling identifies novel gene-environment interactions

    Yu, G., Miller, D. J., Wu, C. T., Hoffman, E. P., Liu, C., Herrington, D. M. & Wang, Y., Dec 1 2019, In : Scientific reports. 9, 1, 2455.

    Research output: Contribution to journalArticle

    Open Access
    Gene-Environment Interaction
    Logistic Models
    Environmental Exposure
    Case-Control Studies
    Health
    Labels
    Experiments

    Flexible inference for cyberbully incident detection

    Zhong, H., Miller, D. J. & Squicciarini, A., Jan 1 2019, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2018, Proceedings. Brefeld, U., Marascu, A., Pinelli, F., Curry, E., MacNamee, B., Hurley, N., Daly, E. & Berlingerio, M. (eds.). Springer Verlag, p. 356-371 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11053 LNAI).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Neural networks
    Sorting
    Output
    Neural Network Model
    Social Networks
    Time series analysis
    decision making
    Time series
    time series analysis
    Decision making
    1 Citation (Scopus)

    Learned Neural Iterative Decoding for Lossy Image Compression Systems

    Ororbia, A. G., Mali, A., Wu, J., O'Connell, S., Dreese, W., Miller, D. J. & Giles, C. L., May 10 2019, Proceedings - DCC 2019: 2019 Data Compression Conference. Marcellin, M. W., Bilgin, A., Storer, J. A. & Serra-Sagrista, J. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 3-12 10 p. 8712688. (Data Compression Conference Proceedings; vol. 2019-March).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Iterative decoding
    Recurrent neural networks
    Image compression
    Decoding
    Color