If you are, like me, confused by why deep neural networks can generalize to out-of-sample data points without drastic overfitting, keep on reading.
If you are, like me, confused by why deep neural networks can generalize to out-of-sample data points without drastic overfitting, keep on reading.
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ay 20 18 The Description Length of Deep Learning Models Léonard Blier École Normale Supérieure Paris, France [email protected] Yann Ollivier Facebook Artificial Intelligence Research ...
Mysteries of Neural Networks Part II
In this year’s ICML, some interesting work was presented on Neural Processes. See the paper conditional Neural Processes and the follow-up work by the same authors on Neural Processes which ...
While feature selection produces a global importance of features with respect to the entire labeled data set, instancewise feature selection mea- sures feature importance locally for each ...
There has been much hype surrounding deep learning and data science learning in recent times, and one of the cornerstones of deep learning is the neural networ…
Artificial neural networks have two main hyperparameters that control the architecture or topology of the network: the number of layers and the number of nodes in each hidden layer. You ...