An information-theoretic analysis of the impact of task similarity on meta-learning
Meta-learning aims at optimizing the hyperparameters of a model class or training algorithm
from the observation of data from a number of related tasks. Following the setting of Baxter …
from the observation of data from a number of related tasks. Following the setting of Baxter …
An Information-Theoretic Analysis of the Impact of Task Similarity on Meta-Learning
ST Jose, O Simeone - … Symposium on Information Theory, ISIT 2021, 2021 - kclpure.kcl.ac.uk
Meta-learning aims at optimizing the hyperparameters of a model class or training algorithm
from the observation of data from a number of related tasks. Following the setting of Baxter …
from the observation of data from a number of related tasks. Following the setting of Baxter …
An Information-Theoretic Analysis of the Impact of Task Similarity on Meta-Learning
ST Jose, O Simeone - arXiv preprint arXiv:2101.08390, 2021 - arxiv.org
Meta-learning aims at optimizing the hyperparameters of a model class or training algorithm
from the observation of data from a number of related tasks. Following the setting of Baxter …
from the observation of data from a number of related tasks. Following the setting of Baxter …
An Information-Theoretic Analysis of the Impact of Task Similarity on Meta-Learning
ST Jose, O Simeone - 2021 IEEE International Symposium on …, 2021 - dl.acm.org
Meta-learning aims at optimizing the hyperparameters of a model class or training algorithm
from the observation of data from a number of related tasks. Following the setting of Baxter …
from the observation of data from a number of related tasks. Following the setting of Baxter …
[PDF][PDF] An Information-Theoretic Analysis of the Impact of Task Similarity on Meta-Learning
ST Jose, O Simeone - researchgate.net
Meta-learning aims at optimizing the hyperparameters of a model class or training algorithm
from the observation of data from a number of related tasks. Following the setting of Baxter …
from the observation of data from a number of related tasks. Following the setting of Baxter …
An Information-Theoretic Analysis of the Impact of Task Similarity on Meta-Learning
ST Jose, O Simeone - arXiv e-prints, 2021 - ui.adsabs.harvard.edu
Meta-learning aims at optimizing the hyperparameters of a model class or training algorithm
from the observation of data from a number of related tasks. Following the setting of Baxter …
from the observation of data from a number of related tasks. Following the setting of Baxter …
An Information-Theoretic Analysis of the Impact of Task Similarity on Meta-Learning
ST Jose, O Simeone - 2021 IEEE International Symposium on …, 2021 - researchwith.njit.edu
Meta-learning aims at optimizing the hyperparameters of a model class or training algorithm
from the observation of data from a number of related tasks. Following the setting of Baxter …
from the observation of data from a number of related tasks. Following the setting of Baxter …
An information-theoretic analysis of the impact of task similarity on meta-learning
S Jose, O Simeone - 2021 IEEE International …, 2021 - research.birmingham.ac.uk
Meta-learning aims at optimizing the hyperparameters of a model class or training algorithm
from the observation of data from a number of related tasks. Following the setting of Baxter …
from the observation of data from a number of related tasks. Following the setting of Baxter …