14 citations · 14 across the 2 of their papers we have counts for
3 papers
Disentangling Domain and Content
Dan Andrei Iliescu, Aliaksei Mikhailiuk, Damon Wischik +1
Many real-world datasets can be divided into groups according to certain salient features (e.g. grouping images by subject, grouping text by font, etc.). Often, machine learning ta…
Training a Task-Specific Image Reconstruction Loss
Aamir Mustafa, Aliaksei Mikhailiuk, Dan Andrei Iliescu +2
The choice of a loss function is an important factor when training neural networks for image restoration problems, such as single image super resolution. The loss function should e…
To Ensemble or Not Ensemble: When does End-To-End Training Fail?
Andrew M. Webb, Charles Reynolds, Wenlin Chen +4
End-to-End training (E2E) is becoming more and more popular to train complex Deep Network architectures. An interesting question is whether this trend will continue-are there any c…