Before revision:  To demonstrate the power and the flexibility of our framework , we apply the framework on three very different learning problems : stochastic gradient descent for strongly convex functions, streaming principal component analysis and linear bandit with stochastic gradient descent updates.
After revision:  To demonstrate the power and the flexibility of our framework by giving unifying analysis for three very different learning problems : stochastic gradient descent for strongly convex functions, streaming principal component analysis and linear bandit with stochastic gradient descent updates.