Browsing Machine Learning Methods in Visualisation for Big Data 2020 by Subject "Computing methodologies"

Now showing items 1-3 of 3

    • ModelSpeX: Model Specification Using Explainable Artificial Intelligence Methods 

      Schlegel, Udo; Cakmak, Eren; Keim, Daniel A. (The Eurographics Association, 2020)
      Explainable artificial intelligence (XAI) methods aim to reveal the non-transparent decision-making mechanisms of black-box models. The evaluation of insight generated by such XAI methods remains challenging as the applied ...

    • Visual Analysis of the Impact of Neural Network Hyper-Parameters 

      Jönsson, Daniel; Eilertsen, Gabriel; Shi, Hezi; Zheng, Jianmin; Ynnerman, Anders; Unger, Jonas (The Eurographics Association, 2020)
      We present an analysis of the impact of hyper-parameters for an ensemble of neural networks using tailored visualization techniques to understand the complicated relationship between hyper-parameters and model performance. ...

    • Visual Interpretation of DNN-based Acoustic Models using Deep Autoencoders 

      Grósz, Tamás; Kurimo, Mikko (The Eurographics Association, 2020)
      In the past few years, Deep Neural Networks (DNN) have become the state-of-the-art solution in several areas, including automatic speech recognition (ASR), unfortunately, they are generally viewed as black boxes. Recently, ...