Expand description
Real-time optimization system for knowledge graph embeddings
This module provides dynamic optimization capabilities that adapt in real-time to improve embedding quality, training efficiency, and inference performance. Features include adaptive learning rates, dynamic architecture optimization, online learning, and intelligent resource management.
Structs§
- Adaptive
Learning Rate Scheduler - Adaptive learning rate scheduler that adjusts based on performance
- Architecture
Config - Architecture
Search Result - Dynamic
Architecture Optimizer - Dynamic architecture optimizer that adjusts model structure
- Learning
Rate Adjustment - Online
Data Point - Online
Learning Config - Online
Learning Manager - Online learning manager for continuous model updates
- Online
Update Result - Optimization
Action - Optimization
Config - Configuration for real-time optimization
- Optimization
History - Optimization history tracking
- Optimization
Summary - Performance
Metrics - Performance metrics tracked by the system
- Performance
Monitor - Performance monitoring system
- Real
Time Optimizer - Real-time optimization engine that continuously improves model performance
- Resource
Allocation - Resource
Optimizer - Resource optimization system
- Resource
Usage