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Network Pruning

21 papers with code ยท Methodology

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Finding Deep Local Optima Using Network Pruning

ICLR 2020

However, in non-vision sparse datasets, especially with many irrelevant features where a standard neural network would overfit, this might not be the case and there might be many non-equivalent local optima.

NETWORK PRUNING

Revisiting the Information Plane

ICLR 2020

It is claimed that Deep Neural Networks in general have good generalization capabilities since they not only learn how to map from an input to an output but also how to compress information about the training data input (Schwartz-Ziv & Tishby, 2017).

NETWORK PRUNING

Neural Epitome Search for Architecture-Agnostic Network Compression

ICLR 2020

In this work, we propose a new perspective on network compression, i. e., network parameters can be disentangled from the architectures.

AUTOML NETWORK PRUNING NEURAL NETWORK COMPRESSION QUANTIZATION

On Iterative Neural Network Pruning, Reinitialization, and the Similarity of Masks

ICLR 2020

We examine how recently documented, fundamental phenomena in deep learn-ing models subject to pruning are affected by changes in the pruning procedure.

NETWORK PRUNING

Privacy Preserving Stochastic Channel-Based Federated Learning with Neural Network Pruning

4 Oct 2019

Artificial neural network has achieved unprecedented success in a wide variety of domains such as classifying, predicting and recognizing objects.

NETWORK PRUNING

ConfusionFlow: A model-agnostic visualization for temporal analysis of classifier confusion

2 Oct 2019

The confusion matrix is an established way for visualizing these class errors, but it was not designed with temporal or comparative analysis in mind.

ACTIVE LEARNING MODEL SELECTION NETWORK PRUNING

Pruning from Scratch

27 Sep 2019

Network pruning is an important research field aiming at reducing computational costs of neural networks.

NETWORK PRUNING

Class-dependent Compression of Deep Neural Networks

23 Sep 2019

Today's deep neural networks require substantial computation resources for their training, storage and inference, which limits their effective use on resource-constrained devices.

NETWORK PRUNING

Architecture-aware Network Pruning for Vision Quality Applications

5 Aug 2019

Convolutional neural network (CNN) delivers impressive achievements in computer vision and machine learning field.

NETWORK PRUNING SUPER RESOLUTION