The problem of least squares regression of a d-dimensional unknown parameter is considered. A stochastic gradient descent based algorithm with weighted iterate-averaging that uses a single pass over ...

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This paper considers the problem of multi-agent distributed linear regression in the presence of system noises. In this problem, the system comprises multiple agents wherein each agent locally ...

Predicting housing prices using linear regression with gradient descent from scratch. Includes data preprocessing, model evaluation, and visualizations like cost function convergence, actual vs pre ...