18563397. TRAINING DEVICE, TRAINING METHOD, AND TRAINING PROGRAM simplified abstract (Nippon Telegraph and Telephone Corporation)
Contents
- 1 TRAINING DEVICE, TRAINING METHOD, AND TRAINING PROGRAM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 TRAINING DEVICE, TRAINING METHOD, AND TRAINING PROGRAM - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about the Technology
- 1.13 Original Abstract Submitted
TRAINING DEVICE, TRAINING METHOD, AND TRAINING PROGRAM
Organization Name
Nippon Telegraph and Telephone Corporation
Inventor(s)
Sekitoshi Kanai of Musashino-shi, Tokyo (JP)
Yasutoshi Ida of Musashino-shi, Tokyo (JP)
TRAINING DEVICE, TRAINING METHOD, AND TRAINING PROGRAM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18563397 titled 'TRAINING DEVICE, TRAINING METHOD, AND TRAINING PROGRAM
Simplified Explanation
A learning device optimizes an objective function in a deep learning model when faced with adversarial attacks by using Entropy-SGD.
Key Features and Innovation
- Learning device calculates objective function in deep learning model.
- Updates parameters to optimize objective function.
- Utilizes Entropy-SGD to handle adversarial attacks.
Potential Applications
This technology can be applied in:
- Cybersecurity to enhance defense against adversarial attacks.
- Image recognition to improve accuracy and robustness.
- Natural language processing for better understanding and interpretation.
Problems Solved
- Enhances security of deep learning models against adversarial attacks.
- Improves the performance and reliability of machine learning systems.
- Mitigates the impact of malicious data inputs on model outcomes.
Benefits
- Increased resilience of deep learning models.
- Enhanced accuracy and efficiency in model optimization.
- Better protection against cyber threats and data manipulation.
Commercial Applications
Title: Enhanced Cybersecurity Solutions with Deep Learning Optimization This technology can be utilized in:
- Security software development for improved threat detection.
- Data analytics tools for more reliable and accurate insights.
- Machine learning platforms for enhanced performance and reliability.
Prior Art
Readers can explore prior research on deep learning model optimization and adversarial attack defense in academic journals and patent databases.
Frequently Updated Research
Stay informed about the latest advancements in deep learning model security and optimization techniques through research publications and conferences.
Questions about the Technology
1. How does the learning device handle adversarial attacks in deep learning models?
The learning device utilizes Entropy-SGD to optimize the objective function and update parameters to enhance model robustness against adversarial attacks.
2. What are the potential real-world applications of this technology?
This technology can be applied in cybersecurity, image recognition, and natural language processing to improve model performance and security.
Original Abstract Submitted
A learning device calculates an objective function when data created as an adversarial attack is input to a deep learning model by Entropy-SGD. The learning device updates parameters of the deep learning model so that an objective function is optimized.
