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07/02/2023
A Proximal Algorithm for Network Slimming
As a popular channel pruning method for convolutional neural networks (C...
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02/10/2023
Feature Affinity Assisted Knowledge Distillation and Quantization of Deep Neural Networks on Label-Free Data
In this paper, we propose a feature affinity (FA) assisted knowledge dis...
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04/16/2022
Searching Intrinsic Dimensions of Vision Transformers
It has been shown by many researchers that transformers perform as well ...
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10/03/2020
Nonconvex Regularization for Network Slimming:Compressing CNNs Even More
In the last decade, convolutional neural networks (CNNs) have evolved to...
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08/10/2020
RARTS: a Relaxed Architecture Search Method
Differentiable architecture search (DARTS) is an effective method for da...
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04/30/2020
TRP: Trained Rank Pruning for Efficient Deep Neural Networks
To enable DNNs on edge devices like mobile phones, low-rank approximatio...
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12/17/2019
ℓ_0 Regularized Structured Sparsity Convolutional Neural Networks
Deepening and widening convolutional neural networks (CNNs) significantl...
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10/24/2019
Weakly-Supervised Degree of Eye-Closeness Estimation
Following recent technological advances there is a growing interest in b...
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10/09/2019
Traned Rank Pruning for Efficient Deep Neural Networks
To accelerate DNNs inference, low-rank approximation has been widely ado...
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03/13/2019
Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets
Training activation quantized neural networks involves minimizing a piec...
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01/24/2019
AutoShuffleNet: Learning Permutation Matrices via an Exact Lipschitz Continuous Penalty in Deep Convolutional Neural Networks
ShuffleNet is a state-of-the-art light weight convolutional neural netwo...
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12/20/2018
DAC: Data-free Automatic Acceleration of Convolutional Networks
Deploying a deep learning model on mobile/IoT devices is a challenging t...
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12/06/2018
Trained Rank Pruning for Efficient Deep Neural Networks
The performance of Deep Neural Networks (DNNs) keeps elevating in recent...
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12/06/2018
DNQ: Dynamic Network Quantization
Network quantization is an effective method for the deployment of neural...
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08/15/2018
Blended Coarse Gradient Descent for Full Quantization of Deep Neural Networks
Quantized deep neural networks (QDNNs) are attractive due to their much ...
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01/19/2018