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Neural Network Compression

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Showing 26–50 of 193 papers

TitleStatusHype
ZeroQ: A Novel Zero Shot Quantization FrameworkCode1
Distilled Split Deep Neural Networks for Edge-Assisted Real-Time SystemsCode1
Learning Filter Basis for Convolutional Neural Network CompressionCode1
Linearity-based neural network compression—0
MUC-G4: Minimal Unsat Core-Guided Incremental Verification for Deep Neural Network Compression—0
Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing—0
Certified Neural Approximations of Nonlinear DynamicsCode0
Low-Rank Matrix Approximation for Neural Network Compression—0
GranQ: Granular Zero-Shot Quantization with Channel-Wise Activation Scaling in QAT—0
Stabilizing Quantization-Aware Training by Implicit-Regularization on Hessian Matrix—0
Compression of Site-Specific Deep Neural Networks for Massive MIMO Precoding—0
A Novel Structure-Agnostic Multi-Objective Approach for Weight-Sharing Compression in Deep Neural Networks—0
What is Left After Distillation? How Knowledge Transfer Impacts Fairness and Bias—0
Efficient and Robust Knowledge Distillation from A Stronger Teacher Based on Correlation Matching—0
Language Models as Zero-shot Lossless Gradient Compressors: Towards General Neural Parameter Prior ModelsCode0
Adaptive Error-Bounded Hierarchical Matrices for Efficient Neural Network Compression—0
TropNNC: Structured Neural Network Compression Using Tropical Geometry—0
Unified Framework for Neural Network Compression via Decomposition and Optimal Rank Selection—0
Convolutional Neural Network Compression Based on Low-Rank Decomposition—0
Condensed Sample-Guided Model Inversion for Knowledge Distillation—0
An Efficient Real-Time Object Detection Framework on Resource-Constricted Hardware Devices via Software and Hardware Co-design—0
Tiled Bit Networks: Sub-Bit Neural Network Compression Through Reuse of Learnable Binary Vectors—0
The Impact of Quantization and Pruning on Deep Reinforcement Learning Models—0
Neural Network Compression for Reinforcement Learning Tasks—0
Towards Explaining Deep Neural Network Compression Through a Probabilistic Latent Space—0
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