online gradient descent
Online gradient descent is a machine learning optimization algorithm that updates model parameters incrementally using small batches of data, adapting to new information received in real time. By learning from each data point individually and continuously refining the model, online gradient descent allows for efficient and scalable training of large datasets.
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Similar Concepts
- accelerated gradient descent methods
- adaptive learning rates in gradient descent
- batch gradient descent
- conjugate gradient descent
- convergence of gradient descent
- gradient descent for linear regression
- gradient descent for neural networks
- hybrid optimization algorithms combining gradient descent
- mini-batch gradient descent
- non-convex optimization using gradient descent
- parallel and distributed gradient descent
- proximal gradient descent
- second-order methods in gradient descent
- stochastic gradient descent
- variants of gradient descent algorithms