Dell products l.p. (20240256853). SYSTEM AND METHOD FOR MANAGING LATENT BIAS IN CLUSTERING BASED INFERENCE MODELS simplified abstract
Contents
SYSTEM AND METHOD FOR MANAGING LATENT BIAS IN CLUSTERING BASED INFERENCE MODELS
Organization Name
Inventor(s)
OFIR Ezrielev of Be'er Sheva (IL)
FATEMEH Azmandian of Raynham MA (US)
SYSTEM AND METHOD FOR MANAGING LATENT BIAS IN CLUSTERING BASED INFERENCE MODELS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240256853 titled 'SYSTEM AND METHOD FOR MANAGING LATENT BIAS IN CLUSTERING BASED INFERENCE MODELS
Simplified Explanation: The patent application discusses methods, systems, and devices for providing computer-implemented services by managing inference models to reduce latent bias.
Key Features and Innovation:
- Managing inference models to reduce latent bias
- Establishing supervised models based on unsupervised learning results
- Training supervised models to reduce latent bias levels
- Analyzing features contributing to latent bias
- Performing supervised learning without consideration for identified features
Potential Applications: This technology can be applied in various fields such as data processing, machine learning, artificial intelligence, and algorithm development.
Problems Solved: This technology addresses the issue of latent bias in inference models used for providing computer-implemented services, ensuring more accurate and unbiased results.
Benefits:
- Improved accuracy in computer-implemented services
- Reduction of latent bias in inference models
- Enhanced fairness and reliability in data processing systems
Commercial Applications: Potential commercial applications of this technology include improving the performance of recommendation systems, enhancing the accuracy of predictive analytics, and optimizing decision-making processes in various industries.
Prior Art: Readers can explore prior research on managing latent bias in inference models, supervised learning techniques, and unsupervised learning methods to understand the existing knowledge in this field.
Frequently Updated Research: Stay updated on the latest advancements in managing latent bias in inference models, supervised learning algorithms, and data processing systems to leverage the most recent innovations in this technology.
Questions about Latent Bias in Inference Models: 1. How does managing inference models help reduce latent bias in computer-implemented services? 2. What are the key steps involved in training supervised models to address latent bias issues?
Original Abstract Submitted
methods, systems, and devices for providing computer-implemented services are disclosed. to provide the computer-implemented services, inference models used by data processing systems may be managed to reduce latent bias. the inference models may be managed by establishing supervised models based on the results of unsupervised learning. the supervised models may then be subjected to training to reduce the levels of latent bias, and analysis to identify features contributing to the latent bias. the supervised learning may then be performed without consideration for the identified features.
