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For a convex quadratic function (like the MSE loss in linear regression), the Lipschitz constant L of the gradient is equal to the largest eigenvalue of the Hessian.

Proof: Let’s define a general convex quadratic function: where , is a symmetric positive semi-definite matrix (to ensure convexity), , and . The gradient of this function is: Lipschitz Continuity A function is Lipschitz continuous… For a convex quadratic function (like the MSE loss in linear regression), the Lipschitz constant L of the gradient is equal to the largest eigenvalue of the Hessian.

Fixed: OSError: You are trying to access a gated repo. Make sure to have access to it at https://huggingface.co….

OSError: You are trying to access a gated repo. Make sure to have access to it at https://huggingface.co/google/gemma-3-27b-it. 401 Client Error. (Request ID: Root=1-67da7d97-6326b5f53a96415516d2c709;7a741876-1aae-4afd-8d26-afd122bc2c2d) Cannot access gated repo for url https://huggingface.co/google/gemma-3-27b-it/resolve/main/config.json. Access to model google/gemma-3-27b-it… Fixed: OSError: You are trying to access a gated repo. Make sure to have access to it at https://huggingface.co….

Principal Components for Neural Network Initialization: A Novel Approach to Explainability and Efficiency

Brief summary: While PCA is traditionally employed for dimensionality reduction and denoising before training, this preprocessing can complicate the interpretability of explainable AI (XAI) methods due to the transformation of input features. To mitigate these… Principal Components for Neural Network Initialization: A Novel Approach to Explainability and Efficiency

Customizing KNN classifier with sklearn

The post describes using custom distance functions with KNeighborsClassifier in scikit-learn. It explains implementing Weighted K-Nearest Neighbors and creating a CustomKNN class, showcasing OOP principles while enhancing KNN functionality and evaluation accuracy.

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Welcome to Nguyen Media. These Terms of Service (“Terms”) govern your access to and use of our website, content, services, and applications. By accessing or using our services, you agree to be bound by these… Terms of Service

Vision-Language Models in Healthcare: Unlocking Multimodal Intelligence for Medical Applications

In summary: Vision-Language Models (VLMs) in healthcare represent a significant technological advancement, offering a promising pathway to integrate and analyze multimodal data, including medical imaging and textual reports, to improve diagnostic accuracy, treatment planning, and… Vision-Language Models in Healthcare: Unlocking Multimodal Intelligence for Medical Applications

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