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cs.LG2019
Reduced-Order Modeling of Deep Neural Networks
Julia Gusak, Talgat Daulbaev, Evgeny Ponomarev +2
We introduce a new method for speeding up the inference of deep neural networks. It is somewhat inspired by the reduced-order modeling techniques for dynamical systems.The cornerst…
cs.LG2019
MUSCO: Multi-Stage Compression of neural networks
Julia Gusak, Maksym Kholiavchenko, Evgeny Ponomarev +3
The low-rank tensor approximation is very promising for the compression of deep neural networks. We propose a new simple and efficient iterative approach, which alternates low-rank…