Matthias Schonlau

‘Less Than One’-Shot Learning: Learning N Classes From M < N Samples

Deep neural networks require large training sets but suffer from high computational cost and long training times. Training on much smaller training sets while maintaining nearly the same accuracy would be very beneficial. In the few-shot learning setting, a model must learn a new class given only a…