Understanding convergence of stochastic gradient descent (SGD) based optimization algorithms can help deal with enormous machine learning problems.

We explore representing complex actions as natural language instructions.

LLMs, but it remains unclear when it helps or hurts.

While contextual bandit has a mature theory, effectively leveraging different feedback patterns to enhance the pace of learning remains unclear.