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Neural Network Compression

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Showing 51–100 of 193 papers

TitleStatusHype
2PFPCE: Two-Phase Filter Pruning Based on Conditional Entropy—0
A Bayesian Optimization Framework for Neural Network Compression—0
ABKD: Graph Neural Network Compression with Attention-Based Knowledge Distillation—0
AcceRL: Policy Acceleration Framework for Deep Reinforcement Learning—0
A Comparative Study of Neural Network Compression—0
A Comprehensive Survey on Model Quantization for Deep Neural Networks in Image Classification—0
Adversarial Network Compression—0
An Efficient Real-Time Object Detection Framework on Resource-Constricted Hardware Devices via Software and Hardware Co-design—0
A novel channel pruning method for deep neural network compression—0
A Novel Structure-Agnostic Multi-Objective Approach for Weight-Sharing Compression in Deep Neural Networks—0
An Overview of Neural Network Compression—0
Approximate Bisimulation Relations for Neural Networks and Application to Assured Neural Network Compression—0
A Survey on Deep Neural Network Compression: Challenges, Overview, and Solutions—0
A Theoretical Understanding of Neural Network Compression from Sparse Linear Approximation—0
Automated Pruning for Deep Neural Network Compression—0
Automatic Parameter Tying in Neural Networks—0
Balanced and Deterministic Weight-sharing Helps Network Performance—0
Boosting the Convergence of Reinforcement Learning-based Auto-pruning Using Historical Data—0
Build a Compact Binary Neural Network through Bit-level Sensitivity and Data Pruning—0
Cascaded Projection: End-to-End Network Compression and Acceleration—0
Combining Compressions for Multiplicative Size Scaling on Natural Language Tasks—0
Compression of Site-Specific Deep Neural Networks for Massive MIMO Precoding—0
Condensed Sample-Guided Model Inversion for Knowledge Distillation—0
Constraint-Aware Deep Neural Network Compression—0
Convolutional Neural Network Compression through Generalized Kronecker Product Decomposition—0
Convolutional Neural Network Compression Based on Low-Rank Decomposition—0
Convolutional neural network compression for natural language processing—0
Model Compression Methods for YOLOv5: A Review—0
Modular Transformers: Compressing Transformers into Modularized Layers for Flexible Efficient Inference—0
MPDCompress - Matrix Permutation Decomposition Algorithm for Deep Neural Network Compression—0
MUC-G4: Minimal Unsat Core-Guided Incremental Verification for Deep Neural Network Compression—0
Multi-head Knowledge Distillation for Model Compression—0
Filter Distillation for Network Compression—0
NETWORK COMPRESSION USING CORRELATION ANALYSIS OF LAYER RESPONSES—0
Neural gradients are near-lognormal: improved quantized and sparse training—0
Neural Network Compression by Joint Sparsity Promotion and Redundancy Reduction—0
Neural Network Compression for Noisy Storage Devices—0
Neural Network Compression for Reinforcement Learning Tasks—0
Neural Network Compression using Binarization and Few Full-Precision Weights—0
Neural Network Compression using Transform Coding and Clustering—0
Neural Network Compression via Effective Filter Analysis and Hierarchical Pruning—0
Neural Network Compression Via Sparse Optimization—0
Noisy Neural Network Compression for Analog Storage Devices—0
Online Multi-target regression trees with stacked leaf models—0
PPCD-GAN: Progressive Pruning and Class-Aware Distillation for Large-Scale Conditional GANs Compression—0
Quantization Aware Factorization for Deep Neural Network Compression—0
Quantization of Generative Adversarial Networks for Efficient Inference: a Methodological Study—0
Quantized Sparse Weight Decomposition for Neural Network Compression—0
Quantum Neural Network Compression—0
Reliable Identification of Redundant Kernels for Convolutional Neural Network Compression—0
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