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Neural Network Compression

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Showing 51–75 of 193 papers

TitleStatusHype
Cascaded Projection: End-to-End Network Compression and Acceleration—0
A Comparative Study of Neural Network Compression—0
AcceRL: Policy Acceleration Framework for Deep Reinforcement Learning—0
A novel channel pruning method for deep neural network compression—0
Differentiable Joint Pruning and Quantization for Hardware Efficiency—0
A Novel Structure-Agnostic Multi-Objective Approach for Weight-Sharing Compression in Deep Neural Networks—0
Cramnet: Layer-wise Deep Neural Network Compression with Knowledge Transfer from a Teacher Network—0
Distilling Critical Paths in Convolutional Neural Networks—0
Coreset-Based Neural Network Compression—0
Distilling Pixel-Wise Feature Similarities for Semantic Segmentation—0
DKM: Differentiable K-Means Clustering Layer for Neural Network Compression—0
DP-Net: Dynamic Programming Guided Deep Neural Network Compression—0
Automated Pruning for Deep Neural Network Compression—0
A Theoretical Understanding of Neural Network Compression from Sparse Linear Approximation—0
Convolutional neural networks compression with low rank and sparse tensor decompositions—0
Adversarial Network Compression—0
Grokking as Compression: A Nonlinear Complexity Perspective—0
Guaranteed Quantization Error Computation for Neural Network Model Compression—0
Convolutional Neural Network Compression via Dynamic Parameter Rank Pruning—0
Convolutional neural network compression for natural language processing—0
Evaluation Metrics for DNNs Compression—0
EPSD: Early Pruning with Self-Distillation for Efficient Model Compression—0
Convolutional Neural Network Compression Based on Low-Rank Decomposition—0
Entropy-Constrained Training of Deep Neural Networks—0
End-to-End Neural Network Compression via _1_2 Regularized Latency Surrogates—0
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