Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation

Mikhail Usvyatsov, Anastasia Makarova, Rafael Ballester-Ripoll +3

We propose an end-to-end trainable framework that processes large-scale visual data tensors by looking at a fraction of their entries only. Our method combines a neural network enc…