AUTOQ: AUTOMATED KERNEL-WISE NEURAL NETWORK QUANTIZATION

Keyphrases

• Inference Accuracy 100%
• Neural Network Quantization 100%
• Convolutional Neural Network 75%
• Learning-based 50%
• Redundancy 50%
• Quantization Technique 50%
• Deep Reinforcement Learning (deep RL) 50%
• Convolutional Layer 50%
• Low Power 25%
• Design Space 25%
• Hardware Efficiency 25%
• Mobile Devices 25%
• Gradient-based 25%
• Energy Consumption 25%
• Energy Overhead 25%
• Hardware Overhead 25%
• Suboptimal Outcome 25%
• Latency Overhead 25%
• Deep Deterministic Policy Gradient 25%
• Neural Network Inference 25%
• Inference Latency 25%
• Activation Layer 25%
• Hierarchical Deep Reinforcement Learning 25%

Computer Science

• Neural Network 100%
• Quantization (Signal Processing) 100%
• Convolutional Neural Network 60%
• Deep Reinforcement Learning 60%
• Convolutional Layer 40%
• Mobile Device 20%
• Energy Consumption 20%
• Hardware Overhead 20%
• Network Inference 20%