1. CSE 312 Foundations of Computing II Instructor: Pedro Domingos

2. Logistics Instructor: Pedro Domingos –Email: pedrod@cs –Office hours: Fridays 2:30-3:20, CSE 648 TA 1: Aniruddh Nath –Email: nath@cs –Office hours: Wednesdays 2:30-3:20, CSE 218 TA 2: Boris Kogon –Email: boris@cs –Office hours: Mondays 3:30-4:20, CSE 216 Web: www.cs.washington.edu/312www.cs.washington.edu/312 Mailing list: cse312a_sp11@uw.edu

3. Evaluation Four homeworks (16% each) –Handed out on Friday on weeks 1, 3, 5 and 7 –Due two before class two weeks later Final (36%)

4. Textbooks D. Bertsekas & J. Tsitsiklis, Introduction to Probability (2 nd ed.), Athena (Required) S. Dasgupta, C. Papadimitriou & U. Vazirani, Algorithms, McGraw-Hill (Required; free online) K. Rosen, Discrete Mathematics and its Applications, (6 th. Ed.), McGraw-Hill (Recommended)

5. What Is this Course About? First 20 lectures: Probability and statistics Last 10 lectures: Algorithms and NP-completeness

6. Why Is Probability Important? Web search Web advertising Spam filtering Collaborative filtering Personalization Machine learning Information integration Sensor networks Performance analysis Algorithm design Scientific data analysis Life in general “Old” CS: Deterministic “New” CS: Probabilistic

7. Probability Counting Basics of probability Conditional probability Random variables Discrete and continuous distributions Expectation and variance Tail bounds and central limit theorem

8. Statistics Maximum likelihood estimation Bayesian estimation Hypothesis testing Linear regression Machine learning

9. Algorithms Polynomial-time algorithms –Divide and conquer –Dynamic programming NP-completeness –Satisfiability –Reductions