In supervised learning, the most prevalent, the data is labeled to tell the machine exactly what patterns it should look for. Think of it as something like a sniffer dog that will hunt down ...

Abstract: In response to the problems of difficulty in information fusion, complex feature learning and difficulty in deep network training in multimodal data, a deep supervised learning algorithm is ...

We present DistillFlow, a knowledge distillation approach to learning optical flow. DistillFlow trains multiple teacher models and a student model, where challenging transformations are applied to the ...

In the formal paper, "data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language," Baevski et al., train the Transformer for image data, speech audio waveforms, and ...