Search
Search Funnelback University
1 -
4 of
4
search results for KA :PC53 24 |u:www.mlmi.eng.cam.ac.uk
where 0
match all words and 4
match some words.
Results that match 2 of 3 words
-
Hierarchical Dialogue Management
https://www.mlmi.eng.cam.ac.uk/files/gordaniello_dissertation.pdf30 Oct 2019: k((bt,at),(bt,at))aTt k̃t1(bt,at) > ν (2.24). where. k̃t1(bt,at) = [k((bt,at),(b̃0,ã0)),.,k((bt,at),(b̃m,ãm))]T. at = K̃1t1k̃t1(bt,at). ... 24 Methods. Figure 3.7. Architecture of the BCM for a set of six domains. -
Optimising spoken dialogue systems using Gaussianprocess…
https://www.mlmi.eng.cam.ac.uk/files/thomas_nicholson_8224691_assignsubmission_file_done.pdf30 Oct 2019: 24. Reducing action selection complexity. 25Clustering of actions. 26. Cold Start. ... The authors use Rollout Classification Policy Itera-tion[24] (RCPI), policy iteration approach that generate training examples by using Monte-Carlo(MC). -
Bayes By Backprop Neural Networks forDialogue Management Christopher…
https://www.mlmi.eng.cam.ac.uk/files/tegho_dissertation.pdf30 Oct 2019: kB(b,b′)kA(a,a. ′) (2.17). The prior for the residual follows Q(b,a) N(0,σ2). ... minibatch. Using Monte Carlo sampling, the expression in 3.15. 24. can be written as:. -
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.pdf25 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
Search history
Recently clicked results
Recently clicked results
Your click history is empty.
Recent searches
Recent searches
Your search history is empty.