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Neural Network Compression

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Showing 51–100 of 193 papers

TitleStatusHype
AcceRL: Policy Acceleration Framework for Deep Reinforcement Learning—0
Partial Binarization of Neural Networks for Budget-Aware Efficient Learning—0
Neural Network Compression by Joint Sparsity Promotion and Redundancy Reduction—0
spred: Solving L_1 Penalty with SGDCode0
Combining Compressions for Multiplicative Size Scaling on Natural Language Tasks—0
Quantized Sparse Weight Decomposition for Neural Network Compression—0
SPIN: An Empirical Evaluation on Sharing Parameters of Isotropic NetworksCode1
Quantum Neural Network Compression—0
A Theoretical Understanding of Neural Network Compression from Sparse Linear Approximation—0
Neural Network Compression via Effective Filter Analysis and Hierarchical Pruning—0
Wavelet Feature Maps Compression for Image-to-Image CNNsCode1
A Comprehensive Survey on Model Quantization for Deep Neural Networks in Image Classification—0
Revisiting Random Channel Pruning for Neural Network CompressionCode0
PPCD-GAN: Progressive Pruning and Class-Aware Distillation for Large-Scale Conditional GANs Compression—0
Approximate Bisimulation Relations for Neural Networks and Application to Assured Neural Network Compression—0
Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint ReductionCode1
Neural Network Compression of ACAS Xu Early Prototype is Unsafe: Closed-Loop Verification through Quantized State BackreachabilityCode0
Toward Compact Parameter Representations for Architecture-Agnostic Neural Network Compression—0
VQN: Variable Quantization Noise for Neural Network Compression—0
CHIP: CHannel Independence-based Pruning for Compact Neural NetworksCode1
NeRV: Neural Representations for VideosCode1
Adaptive Distillation: Aggregating Knowledge from Multiple Paths for Efficient DistillationCode0
Prune Your Model Before Distill ItCode1
Semi-tensor Product-based TensorDecomposition for Neural Network Compression—0
Tropical Geometrical Zonotope Reduction as Applied to Neural Network Compression.—0
Convolutional Neural Network Compression through Generalized Kronecker Product Decomposition—0
Quantization of Generative Adversarial Networks for Efficient Inference: a Methodological Study—0
DKM: Differentiable K-Means Clustering Layer for Neural Network Compression—0
Boosting the Convergence of Reinforcement Learning-based Auto-pruning Using Historical Data—0
Data-Driven Low-Rank Neural Network Compression—0
HEMP: High-order Entropy Minimization for neural network comPression—0
Joint Matrix Decomposition for Deep Convolutional Neural Networks CompressionCode0
Exact Backpropagation in Binary Weighted Networks with Group Weight TransformationsCode0
Minimally Invasive Surgery for Sparse Neural Networks in Contrastive Manner—0
Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and BetterCode1
Efficient Micro-Structured Weight Unification and Pruning for Neural Network Compression—0
Heavy Tails in SGD and Compressibility of Overparametrized Neural NetworksCode0
Towards Compact CNNs via Collaborative CompressionCode0
Data-Free Knowledge Distillation with Soft Targeted Transfer Set Synthesis—0
Spectral Tensor Train Parameterization of Deep Learning LayersCode1
Scaling Up Exact Neural Network Compression by ReLU StabilityCode0
FAT: Learning Low-Bitwidth Parametric Representation via Frequency-Aware TransformationCode1
Neural Network Compression for Noisy Storage Devices—0
UMEC: Unified model and embedding compression for efficient recommendation systems—0
Sparse matrix products for neural network compression—0
Efficient CNN-LSTM based Image Captioning using Neural Network CompressionCode0
Robustness and Transferability of Universal Attacks on Compressed ModelsCode1
Parallel Blockwise Knowledge Distillation for Deep Neural Network CompressionCode0
Multi-head Knowledge Distillation for Model Compression—0
torchdistill: A Modular, Configuration-Driven Framework for Knowledge DistillationCode0
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