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  2. Hierarchical Dialogue Management

    https://www.mlmi.eng.cam.ac.uk/files/gordaniello_dissertation.pdf
    30 Oct 2019: k((b,a),(b,a)) = kB(b,b)kA(a,a) (2.26). Algorithm 2 Implementation of the GPSARSA algorithm.1: Define a prior for Q2: for all dialogues do3: Initialise
  3. Optimising spoken dialogue systems using Gaussianprocess…

    https://www.mlmi.eng.cam.ac.uk/files/thomas_nicholson_8224691_assignsubmission_file_done.pdf
    30 Oct 2019: Optimising spoken dialogue systems using Gaussianprocess reinforcement learning for a large action set. Thomas F. W. Nicholson. Department of engineering. University of Cambridge. M.Phil in Machine Learning, Speech and Language Technology. The
  4. Bayes By Backprop Neural Networks forDialogue Management Christopher…

    https://www.mlmi.eng.cam.ac.uk/files/tegho_dissertation.pdf
    30 Oct 2019: kB(b,b′)kA(a,a. ′) (2.17). The prior for the residual follows Q(b,a) N(0,σ2).
  5. Neural ProcessesGinte Petrulionyte Yuriko Kobe Jack Davis Neural…

    https://www.mlmi.eng.cam.ac.uk/files/2020-2021_advanced_machine_learning_posters/neural_processes_2021.pdf
    25 Jan 2022: Neural ProcessesGinte Petrulionyte Yuriko Kobe Jack Davis. Neural networks (NNs) are effective function approximators, but do not captureuncertainty over their predictions and cannot easily be updated after training. Gaussian Processes (GPs) are

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