Prof. Emo Welzl and Prof. Bernd Gärtner
Bernd Gärtner (CAB G 31.1),
Mohsen Ghaffari (CAB G 32.1),
Angelika Steger (CAB G 37.2),
David Steurer (CAB H 36.2),
Chih-Hung Liu (CAB G 19.3), contact assistant
Hung Phuc Hoang (CAB G 19.2),
Jorge Luis Toro Pozo (CNB F 100.5),
Manuel Wettstein (CAB G 38),
Ahad N. Zehmakan (CAB G 39.3).
Mon 13-15, ML D 28,
Tue 14-16, HG D 1.1.
|Exercise:||You are free to choose whichever group suits you best:
|Credit Points:||8CP for Informatik Bachelor and Mathematik Bachelor (252-0209-00L, 4V + 2U + 1A)|
Advanced design and analysis methods for algorithms and data structures.
Preliminary list of topics:
The Lecture Notes
|Prerequisites:||Familiarity with basic notions of probability theory, cf. the course Algorithmen und Wahrscheinlichkeit. In particular, you should have a good understanding of the notions mentioned in the help sheet for the exam of that course. See also Basics of Probabilistic Analysis for the APC-Lecture.|
There will be an optional written midterm exam and a written final exam. Script or any other supplementary material for either exam is not permitted. Furthermore, we will hand out two special assignments (compulsory continuous performance assessment) whose solution (typeset in LaTeX) is due two weeks later and will be graded.
The final grade is 20% midterm exam + 20% special assignments + 60% final examOR if the result of the midterm exam does not improve the final grade or has not been sitted: 20% special assignments + 80% final exam.
|Oct 15 - Oct 29 at 2:15 pm.||
| On Monday, November 4, instead of the
No written material will be permitted. The exam covers all material up to the lecture on October 29. You may find previous midterms here: 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017. 2018.
Absence. If there are compelling reasons why you cannot hand in a special assignment on the due date foreseen, please contact us post-haste and we can look for a solution. Note, however, that we will grant requests of this type only in very exceptional cases (doctor's note, military service, funeral, etc.). Private events (vacation, sports, career fairs, etc.) are never sufficient grounds. As far as special assignments are concerned, you can hand them in to the contact assistant by email at any time before the due date, so there is no need to be present in person. As regards the final exam, ETH regulations apply.
Exchange students. Exchange students enrolled for APC in fall might want to return to their home university prior to the date of the final exam. If this applies to you and you nonetheless wish to be evaluated and given credits for APC, then as an alternative to returning to Zurich for the exam, there is the possibility for you to take the exam at your home university at the same time it takes place in Zurich. If you want to make use of this exam mode, you as a student are responsible for finding a professor at your home university who is willing to allocate resources for such a supervision and for establishing contact between us and the other party. At any rate, arrangements of this type have to be made very timely, preferably at the beginning of the semester. If you contact us too late, we cannot help you.
Regular exercises are made available online on a weekly basis. Students are expected to (try and) solve the problems and attend the exercise classes. Your assistant is happy to look at your solutions and correct/comment them. All exercises and their solutions are part of the material relevant for the two exams.
In the table below you can find the lecture dates and the preliminary topics. The exercises and their solutions will be published here.
|Calendar Week||Date||Topic||Exercises and SPAs
(by due date)
|No class. As a preparation to this week's exercises, please read Basics of Probabilistic Analysis.||ex-KW38.pdf (only in-class exercises, no hand-in date)||solution-KW38.pdf|
|Bootstrapping Techniques (1.1) Slides|
|Bootstrapping Techniques (1.2)||ex-KW39.pdf (updated 23.09.2019 for a typo in Exercise~2.ii.a)||solution-KW39.pdf (updated 27.09.2019)|
|Random(ized) Search Trees (2.1) Slides|
|Random(ized) Search Trees (2.2, 2.3, and 2.4)||ex-KW40.pdf (updated 30.09 for Exercise 3(c))||solution-KW40.pdf|
|Random(ized) Search Trees (2.5 and 2.7)|
|Point Location (3.1)||ex-KW41.pdf||solution-KW41.pdf|
|Point Location (3.2 and 3.3)|
|Point Location (3.4)||ex-KW42.pdf||solution-KW42.pdf|
|Linear Programming (4.1 and 4.2)|
|Linear Programming (4.3)||ex-KW43.pdf (in-class)|
|Linear Programming (4.4)|
|Linear Programming (4.5)||Special Assignment 1|
|Linear Programming (4.6)|