Search Results for author:
Found 4 papers, 0 papers with code
The Sample Complexity Of ERMs In Stochastic Convex Optimization
In this work we show that in fact $\tilde{O}(\frac{d}{\epsilon}+\frac{1}{\epsilon^2})$ data points are also sufficient.
A Characterization of Multiclass Learnability
This work resolves this problem: we characterize multiclass PAC learnability through the DS dimension, a combinatorial dimension defined by Daniely and Shalev-Shwartz (2014).
Learning Infinite Layer Networks without the Kernel Trick
Infinite Layer Networks (ILN) have been proposed as an architecture that mimics neural networks while enjoying some of the advantages of kernel methods.
Learning Infinite-Layer Networks: Without the Kernel Trick
Infinite--Layer Networks (ILN) have recently been proposed as an architecture that mimics neural networks while enjoying some of the advantages of kernel methods.
