Pu­bli­ka­tio­nen

[ 2022 ] [ 2021 ] [ 2017 ]

2022 [ nach oben ]

  • 1.
    Guo, T., Huang, Z., Cheng, J.: LwTool: A data processing toolkit for building a real-time pressure mapping smart textile software system. Pervasive and Mobile Computing. 80, 101540 (2022).
     
  • 2.
    Herde, M., Huang, Z., Huseljic, D., Kottke, D., Vogt, S., Sick, B.: Fast Bayesian Updates for Deep Learning with a Use Case in Active Learning. arXiv e-prints. arXiv:2210.06112 (2022).
     
  • 3.
    He, Y., Huang, Z., Sick, B.: Design of Explainability Module with Experts in the Loop for Visualization and Dynamic Adjustment of Continual Learning. Workshop on Interactive Machine Learning Workshop (IMLW), AAAI. bll. 1–6 (2022).
     
  • 4.
    Huang, Z.: Active Learning in Multivariate Time Series Anomaly Detection. In: Tomforde, S. en Krupitzer, C. (reds.) Organic Computing -- Doctoral Dissertation Colloquium 2021. bll. 113–124. kassel university press (2022).
     

2021 [ nach oben ]

  • 1.
    Huang, Z., He, Y., Vogt, S., Sick, B.: Uncertainty and Utility Sampling with Pre-Clustering. Workshop on Interactive Adaptive Learning (IAL), ECML PKDD (2021).
     
  • 2.
    He, Y., Huang, Z., Sick, B.: Toward Application of Continuous Power Forecasts in a Regional Flexibility Market. International Joint Conference on Neural Networks (IJCNN). bll. 1–8. IEEE (2021).
     
  • 3.
    Gruhl, C., Hannan, A., Huang, Z., Nivarthi, C., Vogt, S.: The Problem with Real-World Novelty Detection -- Issues in Multivariate Probabilistic Models. Workshop on Self-Improving System Integration (SISSY), ACSOS. bll. 204–209. IEEE (2021).
     

2017 [ nach oben ]

  • 1.
    Zhou, B., Cheng, J., Mawandia, A., He, Y., Huang, Z., Sundholm, M., Yildrim, M., Cruz, H., Lukowicz, P.: TPM Framework: a Comprehensive Kit for Exploring Applications with Textile Pressure Mapping Matrix. International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies (UBICOMM). IARIA (2017).