UIUC CS 374 FA 20: 23.1.2. SAT is NP-Complete

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UIUC CS 374 FA 20: 23.1.2. SAT is NP-Complete
  1. Sariel Har-Peled
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UIUC CS 374 0:09:33

UIUC CS 374 FA 20: 5.1.2. Algorithms for converting NFA to DFA

UIUC CS 374 0:04:48

UIUC CS 374 FA 20: 20.6.1. Implementing Borůvka’s Algorithm

UIUC CS 374 0:13:16

UIUC CS 374 FA 20: 13.2. Dynamic programming

UIUC CS 374 0:12:49

UIUC CS 374 FA 20: 5.1. Equivalence of NFAs and DFAs (introduction)

UIUC CS 374 0:32:56

UIUC CS 374 FA 20 1.4 Languages

UIUC CS 374 0:04:42

UIUC CS 374 FA 20: 8.4. Languages defined by a Turing machine

UIUC CS 374 0:06:30

UIUC CS 374 FA 20: 4.4. Every regular language has an NFA

UIUC CS 374 0:07:15

UIUC CS 374 FA 20: 23.1.2. SAT is NP-Complete

UIUC CS 374 0:08:13

UIUC CS 374 FA 20: 10.2. What is a good algorithm?

UIUC CS 374 0:10:55

UIUC CS 374 FA 20: 3.1. Introduction to DFAs

UIUC CS 374 0:20:16

UIUC CS 374 FA 20: 3.2 Constructing DFAs

UIUC CS 374 0:11:21

UIUC CS 374 FA 20: 4.2. Constructing NFAs

UIUC CS 374 0:08:01

UIUC CS 374 FA 20 2.1 Regular Languages

UIUC CS 374 0:03:29

UIUC CS 374 FA 20: 7.6. CFGs normal form

UIUC CS 374 0:09:28

UIUC CS 374 FA 20: 3.1.1 Graphical representation of DFAs

UIUC CS 374 0:10:01

UIUC CS 374 FA 20: 23.1.1. Completeness

UIUC CS 374 0:05:29

UIUC CS 374 FA 20: 4.1.1 Formal definition of NFAs

UIUC CS 374 0:17:10

UIUC CS 374 FA 20: 3.4. Product construction for DFAs

UIUC CS 374 0:04:24

UIUC CS 374 FA 20: 3.3. How to build a DFA for the complement language

UIUC CS 374 0:08:01

UIUC CS 374 FA 20: 10.8. Binary search

UIUC CS 374 0:05:31

UIUC CS 374 FA 20: 9.4. TM Unrecongizable

UIUC CS 374 0:06:52

UIUC CS 374 FA 20: 6.4. Using closure properties to prove non-regularity

UIUC CS 374 0:08:55

UIUC CS 374 FA 20: 5.2. Closure properties of regular languages

UIUC CS 374 0:05:21

UIUC CS 374 FA 20: 22.2.2. Certifiers/Verifiers