Propose an alternative optimization algorithm or approach to handle this worst-case scenario while ensuring efficient computation and minimizing redundant work. Explain the tradeoff.

Consider using a hybrid approach that switches between minibatch stochastic gradient descent and batch gradient descent based on the dataset’s redundancy level. This would adaptively adjust the computational cost and ensure efficient processing even when all m samples are identical.