Tight Lower Bound on the Probability of a Binomial Exceeding its Expectation

This provides a foundational inequality for analyzing relative deviation bounds in learning theory, addressing a core problem in statistical learning theory.

The paper proves a tight lower bound on the probability that a binomial random variable exceeds its expected value, with the bound being exact and applicable in contexts like learning theory and generalization bounds.