What is computation? What can be computed in principle with unbounded computational resources? What can be computed efficiently? What can we gain by formally modeling computation and how do different models relate to one another? How can models highlight different resources of computations, some obvious (such as time and memory) and others less so (such as communication and randomness). What is gained by considering natural and social phenomenon as computations and looking at central notions such as proofs, knowledge, learning, games, randomness, entropy and more through the computational lens?
We will consider these questions and others using a rigorous mathematical approach. We will discuss what we know as well as some of the central open problems in pure and applied mathematics, and specifically the P vs. NP problem.
Some specific topics: Finite Automata – Very Simple Models (constant memory), Non-determinism (power of guessing), Learning, communication complexity, Streaming algorithms, Powerful models – Turing Machines, Decidability, Kolmogorov Complexity, Time complexity, P vs. NP, NP-completeness, Other Resources: space, randomness, communication, power, … Crypto, Game Theory, … The Computational Lens.
Prerequisites: CS 103 or 103B.
Current Offering: Fall 2017
Instructor: Omer Reingold, Gates 462, reingold (at stanford dot edu)
Saba Eskandarian, sabae (at stanford dot edu)
Matthew Jay Katzman, mkatzman (at stanford dot edu)
Daniel Layton Wright, dlwright (at stanford dot edu)
Jimmy Wu, jimmyjwu (at stanford dot edu)
Location and Times:
Tue, Thu 10:30 AM – 11:50 AM at Skilling Auditorium (494 Lomita Mall Stanford)
Book: Michael Sipser, introduction to the theory of computation (2nd or 3rd edition)
Office Hours: Follow on Piazza
HW assignments (follow on Piazza):
Homework will be assigned every Tuesday (except for the week before the midterm) and will be due one week later at the beginning of class. No late submission. We will drop your lowest homework grade
You may (even encouraged to) collaborate with others, but you must:
1. Try to solve all the problems by yourself first
2. List your collaborators on each problem
3. If you receive a significant idea from somewhere, you must acknowledge that source in your solution.
4. Write your own solutions (important!)
Assignments and submissions through gradescope.com
Best to write in LaTex
Grades: Will be at least a combination of 45% HW assignments, 25% midterm, 30% finals
Tuesday 9/26: Introduction
What are computations? The Computational Lens. Course information and topics. Why Theory? The most fundamental open question of CS: graph coloring ?!? Proof techniques (and an example).
Reading: Chapter 0, Introduction, Sipser
What between Ogres, Onions, Parfait, and good proofs?
Thursday 9/28: Deterministic Finite Automata, Closure Properties, Nondeterminism
Reading (for next few classes): Chapter 1, Sipser
Tuesday 10/3: Finish closure properties of regular languages, Show equivalence of DFSa and NFAs, define regular expression and characterize the languages they correspond to.
Thursday 10/5: Non-Regular Languages, The Pumping Lemma, An Algorithm for Minimizing a DFA
Reading: Chapter 1.4, Sipser; A note on DFA minimization and Myhill-Nerode
Tuesday 10/10: Finish Minimizing FDA, The Myhill-Nerode Theorem
Thursday 10/12: Learning DFAs, Streaming Algorithms
No new PPTX
- Angluin’s classic paper on learning DFAs
- A note on streaming Algorithms;
- Article on finding frequent elements
Tuesday 10/17: Communication Complexity; Starting Turing Machines: deciding vs. recognizing
- Sipser Section 4, 5
Tuesday 10/31: in-class midterm
Tuesday 11/21: Thanksgiving – no class
Thursday 11/23: Thanksgiving – no class
Wednesday, December 13, 12:15-3:15 p.m: Finals