By the tower property for conditional expectations, the second term reduces to:
Conditional probability may be treated as a special case of conditional expectation.
For example, it can be used to prove the existence of conditional expectation for probability measures.
Further, this simple algorithm can also be easily derandomized using the method of conditional expectations.
In addition, there is also a version for conditional expectations.
Given that some of the vertices are colored already, what is this conditional expectation?
Consequently, the current observation provides support from below the future conditional expectation, and the process tends to increase in future time.
More formally, this result is obtained using conditional expectation.
This is not a constructive definition; we are merely given the required property that a conditional expectation must satisfy.
To do this, it suffices to keep the conditional expectation of from increasing.