Title: Theory / Unimportant / CS / Fundamental / Complexity / Wigderson / 17 Computational learning theory, AI and beyond
Tags: fromAlgorithm hasNotNewEffectReturnsMeaning

Page: 213
Implementation: Assign to each word \(j\) a «spam-weight» \(h(j)\). Let \(x(j)\) the number of occurrence of \(j\) in an email.
Compute \(\langle h,x\rangle\), declare it spam if it is greater than some constant \(v\)
Section: 1
Chapter: 17
Effect: Simple model to detect spam

Question: Why can we limit ourself to hyperplane going through 0.
Answer: A hyperplane not going through \(0\) belongs to a hyperplane going through 0 in a space with one more dimension
Page: 213
Chapter: 17
Section: 1

Name: Classification problem
Definition: An on-line problem in which the algorithm observing the sequence should propose a hypothesis for \(h^*\) after seeing every new example.
Page: 213
Chapter: 17
Section: 1