18124999. FEDERATED LEARNING TECHNIQUE simplified abstract (NVIDIA CORPORATION)
Contents
FEDERATED LEARNING TECHNIQUE
Organization Name
Inventor(s)
Holger Reinhard Roth of Rockville MD (US)
Dong Yang of Pocatello ID (US)
Vishwesh Nath of Nashville TN (US)
FEDERATED LEARNING TECHNIQUE - A simplified explanation of the abstract
This abstract first appeared for US patent application 18124999 titled 'FEDERATED LEARNING TECHNIQUE
Simplified Explanation: The patent application describes apparatuses, systems, and techniques for training and using neural networks, with a focus on aggregating training data based on contributions and performance metrics.
Key Features and Innovation:
- Processor with circuits for aggregating neural network training data.
- Consideration of contribution of training data and performance metrics.
- Focus on improving neural network training efficiency and effectiveness.
Potential Applications: This technology can be applied in various fields such as:
- Machine learning
- Artificial intelligence
- Data analysis
- Pattern recognition
Problems Solved: The technology addresses challenges such as:
- Enhancing neural network training processes
- Improving the accuracy and performance of neural networks
- Streamlining data aggregation for training purposes
Benefits:
- Increased efficiency in neural network training
- Enhanced performance and accuracy of neural networks
- Better utilization of training data for improved outcomes
Commercial Applications: Potential commercial uses include:
- Developing advanced AI systems
- Enhancing data analysis tools
- Improving pattern recognition software
- Optimizing machine learning algorithms
Questions about Neural Network Training Technology: 1. How does this technology improve the efficiency of neural network training? 2. What are the key factors considered in aggregating neural network training data?
Frequently Updated Research: Stay updated on the latest advancements in neural network training techniques and technologies to ensure optimal performance and results.
Original Abstract Submitted
Apparatuses, systems, and techniques to train/use one or more neural networks. In at least one embodiment, a processor comprises one or more circuits to cause neural network training information to be aggregated based, at least in part, on contribution of the neural network training data and one or more performance metrics of the neural network.
