Linearly Replaceable Filters for Deep Network Channel Pruning 编辑：牛涛
Neural Network Pruning with Residual-Connections and Limited-Data 编辑：牛涛
LAYER-ADAPTIVE SPARSITY FOR THE MAGNITUDE-BASED PRUNING 编辑：牛涛
EagleEye: Fast Sub-net Evaluation for Efficient Neural Network Pruning 编辑：牛涛
Model Compression Based on Differentiable Network Channel Pruning 编辑：牛涛
Filter Pruning by Switching to Neighboring CNNs With Good Attributes 编辑：牛涛
GDP: Stabilized Neural Network Pruning via Gates with Differentiable Polarization 编辑：牛涛
Feature Statistics Guided Efficient Filter Pruning 编辑：牛涛
Filter Sketch for Network Pruning 编辑：牛涛
Accelerate CNNs from Three Dimensions: A Comprehensive Pruning Framework 编辑：牛涛
Manifold Regularized Dynamic Network Pruning 编辑：牛涛
Network pruning via Performance Maximization 编辑：牛涛
Attention-based pruning for shift networks 编辑：牛涛
HRank: Filter Pruning using High-Rank Feature Map 编辑：牛涛
Holistic Filter Pruning for Efficient Deep Neural Networks 编辑：牛涛
Dynamic Channel Pruning: Feature Boosting and Suppression 编辑：牛涛
PRUNING FILTER IN FILTER 编辑：牛涛
Neuron-level Structured Pruning using Polarization Regularizer 编辑：牛涛
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression 编辑：牛涛
Learning Filter Pruning Criteria for Deep Convolutional Neural Networks Acceleration 编辑：牛涛
DMCP: Differentiable Markov Channel Pruning for Neural Networks 编辑：牛涛
MORE-SIMILAR-LESS-IMPORTANT: FILTER PRUNING VIA KMEANS CLUSTERING 编辑：牛涛
Soft and Hard Filter Pruning via Dimension Reduction 编辑：牛涛
AutoPruning for Deep Neural Network with Dynamic Channel Masking 编辑：牛涛
Softer Pruning, Incremental Regularization 编辑：牛涛
Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks 编辑：牛涛
An Entropy-based Pruning Method for CNN Compression 编辑：牛涛
SCOP: Scientific Control for Reliable Neural Network Pruning 编辑：牛涛
DropNet: Reducing Neural Network Complexity via Iterative Pruning 编辑：牛涛
Global Sparse Momentum SGD for Pruning Very Deep Neural Networks 编辑：牛涛
Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks 编辑：牛涛
Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration 编辑：牛涛
SNIP: SINGLE-SHOT NETWORK PRUNING BASED ON CONNECTION SENSITIVITY 编辑：牛涛
AUTOPRUNING FOR DEEP NEURAL NETWORK WITH DYNAMIC CHANNEL MASKING 编辑：牛涛
Channel Pruning via Automatic Structure Search 编辑：牛涛
Coreset-Based Neural Network Compression 编辑：牛涛
AMC: AutoML for Model Compression and Acceleration on Mobile Devices 编辑：牛涛
Accelerating Convolutional Networks via Global & Dynamic Filter Pruning 编辑：牛涛
Discrimination-aware Channel Pruning for Deep Neural Networks 编辑：牛涛
RETHINKING THE VALUE OF NETWORK PRUNING 编辑：牛涛
Channel Pruning for Accelerating Very Deep Neural Networks 编辑：牛涛
ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression 编辑：牛涛
Dynamic Network Surgery for Efficient DNNs 编辑：牛涛
PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning 编辑：牛涛
Learning Efficient Convolutional Networks through Network Slimming 编辑：牛涛
Network Trimming: A Data-Driven Neuron Pruning Approach towards Efficient Deep Architectures 编辑：牛涛
PRUNING FILTERS FOR EFFICIENT CONVNETS 编辑：牛涛
Learning both Weights and Connections for Efficient Neural Networks 编辑：牛涛
Asymptotic Soft Filter Pruning for Deep Convolutional Neural Networks 编辑：牛涛
Learning Structured Sparsity in Deep Neural Networks 编辑：牛涛
MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning 编辑：牛涛
