3.1k citations · 8.3k across the 43 of their papers we have counts for
5 papers · 1 filter
Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition
Vadim Lebedev, Yaroslav Ganin, Maksim Rakhuba +2
We propose a simple two-step approach for speeding up convolution layers within large convolutional neural networks based on tensor decomposition and discriminative fine-tuning. Gi…
Unsupervised Domain Adaptation by Backpropagation
Yaroslav Ganin, Victor Lempitsky
Top-performing deep architectures are trained on massive amounts of labeled data. In the absence of labeled data for a certain task, domain adaptation often provides an attractive…
-Fields: Neural Network Nearest Neighbor Fields for Image Transforms
Yaroslav Ganin, Victor Lempitsky
We propose a new architecture for difficult image processing operations, such as natural edge detection or thin object segmentation. The architecture is based on a simple combinati…
Improving Bilayer Product Quantization for Billion-Scale Approximate Nearest Neighbors in High Dimensions
Artem Babenko, Victor Lempitsky
The top-performing systems for billion-scale high-dimensional approximate nearest neighbor (ANN) search are all based on two-layer architectures that include an indexing structure…
Neural Codes for Image Retrieval
Artem Babenko, Anton Slesarev, Alexandr Chigorin +1
It has been shown that the activations invoked by an image within the top layers of a large convolutional neural network provide a high-level descriptor of the visual content of th…