Julia Gusak | DeepAI

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∙ 08/08/2023

Quantization Aware Factorization for Deep Neural Network Compression

Tensor decomposition of convolutional and fully-connected layers is an e...

0 Daria Cherniuk, et al. ∙

∙ 07/03/2023

Rockmate: an Efficient, Fast, Automatic and Generic Tool for Re-materialization in PyTorch

We propose Rockmate to control the memory requirements when training PyT...

0 Xunyi Zhao, et al. ∙

∙ 06/05/2023

Efficient GPT Model Pre-training using Tensor Train Matrix Representation

Large-scale transformer models have shown remarkable performance in lang...

0 Viktoriia Chekalina, et al. ∙

∙ 02/21/2022

Survey on Large Scale Neural Network Training

Modern Deep Neural Networks (DNNs) require significant memory to store w...

0 Julia Gusak, et al. ∙

∙ 02/01/2022

Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction

Memory footprint is one of the main limiting factors for large neural ne...

0 Georgii Novikov, et al. ∙

∙ 01/31/2022

Memory-Efficient Backpropagation through Large Linear Layers

In modern neural networks like Transformers, linear layers require signi...

0 Daniel Bershatsky, et al. ∙

∙ 03/15/2021

Meta-Solver for Neural Ordinary Differential Equations

A conventional approach to train neural ordinary differential equations ...

0 Julia Gusak, et al. ∙

∙ 08/12/2020

Stable Low-rank Tensor Decomposition for Compression of Convolutional Neural Network

Most state of the art deep neural networks are overparameterized and exh...

7 Anh-Huy Phan, et al. ∙

∙ 04/20/2020

Towards Understanding Normalization in Neural ODEs

Normalization is an important and vastly investigated technique in deep ...

2 Julia Gusak, et al. ∙

∙ 03/11/2020

Interpolated Adjoint Method for Neural ODEs

In this paper, we propose a method, which allows us to alleviate or comp...

12 Talgat Daulbaev, et al. ∙

∙ 10/29/2019

Active Subspace of Neural Networks: Structural Analysis and Universal Attacks

Active subspace is a model reduction method widely used in the uncertain...

33 Chunfeng Cui, et al. ∙

∙ 10/15/2019

Reduced-Order Modeling of Deep Neural Networks

We introduce a new method for speeding up the inference of deep neural n...

0 Talgat Daulbaev, et al. ∙

∙ 03/24/2019

One time is not enough: iterative tensor decomposition for neural network compression

The low-rank tensor approximation is very promising for the compression ...

24 Julia Gusak, et al. ∙

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