355 citations · 1.6k across the 54 of their papers we have counts for
5 papers · 1 filter
Double descent in the condition number
Tomaso Poggio, Gil Kur, Andrzej Banburski
In solving a system of linear equations in variables , the condition number of the matrix measures how much errors in the data affect the solution .…
Theoretical Issues in Deep Networks: Approximation, Optimization and Generalization
Tomaso Poggio, Andrzej Banburski, Qianli Liao
While deep learning is successful in a number of applications, it is not yet well understood theoretically. A satisfactory theoretical characterization of deep learning however, is…
Deep Recurrent Architectures for Seismic Tomography
Amir Adler, Mauricio Araya-Polo, Tomaso Poggio
This paper introduces novel deep recurrent neural network architectures for Velocity Model Building (VMB), which is beyond what Araya-Polo et al 2018 pioneered with the Machine Lea…
Function approximation by deep networks
H. N. Mhaskar, T. Poggio
We show that deep networks are better than shallow networks at approximating functions that can be expressed as a composition of functions described by a directed acyclic graph, be…
Theory III: Dynamics and Generalization in Deep Networks
Andrzej Banburski, Qianli Liao, Brando Miranda +4
The key to generalization is controlling the complexity of the network. However, there is no obvious control of complexity -- such as an explicit regularization term -- in the trai…