1 citations · 1 across the 1 of their papers we have counts for
4 papers
Post-training deep neural network pruning via layer-wise calibration
Ivan Lazarevich, Alexander Kozlov, Nikita Malinin
We present a post-training weight pruning method for deep neural networks that achieves accuracy levels tolerable for the production setting and that is sufficiently fast to be run…
Neural Network Compression Framework for fast model inference
Alexander Kozlov, Ivan Lazarevich, Vasily Shamporov +2
In this work we present a new framework for neural networks compression with fine-tuning, which we called Neural Network Compression Framework (NNCF). It leverages recent advances…
Stock market microstructure inference via multi-agent reinforcement learning
J. Lussange, I. Lazarevich, S. Bourgeois-Gironde +2
Quantitative finance has had a long tradition of a bottom-up approach to complex systems inference via multi-agent systems (MAS). These statistical tools are based on modelling age…
Dynamics of the brain extracellular matrix governed by interactions with neural cells
Ivan Lazarevich, Sergey Stasenko, Maia Rozhnova +3
Neuronal and glial cells release diverse proteoglycans and glycoproteins, which aggregate in the extracellular space and form the extracellular matrix (ECM) that may in turn regula…