no code implementations • 10 Nov 2013 • Amit Daniely, Nati Linial, Shai Shalev-Shwartz
The biggest challenge in proving complexity results is to establish hardness of {\em improper learning} (a. k. a.
no code implementations • NeurIPS 2013 • Amit Daniely, Nati Linial, Shai Shalev Shwartz
That is, if more data is available, beyond the sample complexity limit, is it possible to use the extra examples to speed up the computation time required to perform the learning task?
no code implementations • 3 Nov 2012 • Amit Daniely, Nati Linial, Shai Shalev-Shwartz
The best approximation ratio achievable by an efficient algorithm is $O\left(\frac{1/\gamma}{\sqrt{\log(1/\gamma)}}\right)$ and is achieved using an algorithm from the above class.