Google llc (20240256873). TRAINING NEURAL NETWORKS BY RESETTING DORMANT NEURONS simplified abstract
Contents
TRAINING NEURAL NETWORKS BY RESETTING DORMANT NEURONS
Organization Name
Inventor(s)
Pablo Samuel Castro Rivadeneira of Ottawa (CA)
Ghada AbdElRahman Zaki Nabawy Sokar of Eindhoven (NL)
Rishabh Agarwal of Montreal (CA)
TRAINING NEURAL NETWORKS BY RESETTING DORMANT NEURONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240256873 titled 'TRAINING NEURAL NETWORKS BY RESETTING DORMANT NEURONS
Simplified Explanation: The patent application describes methods, systems, and apparatus for training a neural network by resetting dormant neurons during the training process.
- Neural network training involves resetting dormant neurons.
- Computer programs are encoded on computer storage media for implementation.
- The innovation aims to optimize neural network performance by resetting dormant neurons.
Key Features and Innovation:
- Training a neural network by resetting dormant neurons.
- Computer programs encoded on storage media for implementation.
- Optimization of neural network performance through resetting dormant neurons.
Potential Applications: The technology can be applied in various fields such as:
- Artificial intelligence
- Machine learning
- Data analysis
Problems Solved: The technology addresses the following issues:
- Improving neural network performance
- Enhancing training efficiency
- Optimizing data processing
Benefits: The technology offers the following benefits:
- Improved accuracy in neural network predictions
- Faster training process
- Enhanced overall performance
Commercial Applications: Potential commercial uses and market implications include:
- Development of advanced AI systems
- Optimization of data analysis processes
- Implementation in various industries for improved efficiency
Questions about Neural Network Training with Dormant Neurons: 1. How does resetting dormant neurons improve neural network performance? 2. What are the potential challenges in implementing this technology in real-world applications?
Frequently Updated Research: Stay updated on the latest advancements in neural network training techniques and optimization strategies to enhance the performance of AI systems.
Original Abstract Submitted
methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network and, during the training, resetting neurons that have been classified as being dormant.
