[图书][B] Advances in Machine Learning: Nearest Neighbour Search, Learning to Optimize and Generative Modelling
K Li - 2019 - search.proquest.com
… We start with limitations on computational efficiency. Many … bound on the log-likelihood
when the model class is richly … , I learned about probabilistic models and Perturb-and-MAP at a …
when the model class is richly … , I learned about probabilistic models and Perturb-and-MAP at a …
Inductive Biases for Deep Linguistic Structured Prediction with Independent Factorization
J Cao - 2022 - search.proquest.com
… to new environments makes us efficiently learn when interacting with the … By combining
Perturb-and-MAP sampling [51] with differentiable … When modeling the negative log likelihood …
Perturb-and-MAP sampling [51] with differentiable … When modeling the negative log likelihood …
[PDF][PDF] A Complete Bibliography of Publications in Statistics and Probability Letters: 2010–2019
NHF Beebe - 2023 - ctan.math.utah.edu
… Efficiency … model-free [CZCL19, KS17a]. Modeling …
[PDF][PDF] Biologically inspired Deep Learning/submitted by Simon Schmid
S Schmid - 2019 - epub.jku.at
… The resulting model can very efficiently learn from very few … based on the perturb and MAP
framework (Papandreou and … F(θ, q(z|y)) is the lower bound for the log-likelihood of the data…
framework (Papandreou and … F(θ, q(z|y)) is the lower bound for the log-likelihood of the data…