TDA251/DIT281, Period 2, 2020: Algorithms Advanced Course
- Emil Carlsson, caremil(at)chalmers.se
- Jeremy Pope, popje(at)chalmers.se
- Hannes Gustafsson (student TA)
- This is a backup page besides the Canvas page.
- Home exam problem specification and instructions.
- (Peter) I remain reachable by mail, but response times may be longer between 23 December and 3 January.
- Thursday, 14 January, 23:59: Deadline for the home exam and for all assignment resubmissions.
Due to the exceptional circumstances, it consists of these components:
Self-study of Notes that are provided in advance. Please do not hesitate to
email questions to the instructor, at any time, and about all points that are
unclear to you.
Online sessions starting on Mondays 13:15 and Thursdays 10:00. They are used for question hours, summarizing lectures of more central or more difficult
topics, and maybe other forms upon need. Details will be announced continuously
in the Announcements section above.
Compulsory assignments (as in normal years) which are part of the grading but also a major part of the learning process.
Numbers in parantheses are corresponding sections in the textbook. Note that not all topics appear in the textbook.
- Lecture 1. Approximation algorithms. Examples: Load
Balancing (11.1). Center Selection (11.2).
- Lecture 2. Approximation algorithm for Set Cover (11.3).
Pricing method - example: Vertex Cover (11.4).
- Lecture 3. Approximation scheme for Knapsack (11.8).
Approximation by linear programming (11.6).
- Lecture 4. Reductions and approximation ratios.
Network flows and cuts (7.1-7.3).
- Lecture 5. Bipartite Matching (7.5). Disjoint Paths (7.6).
Circulations (7.7). Applications of flows: survey design (7.8).
- Lecture 6. Airline scheduling (7.9). Applications of cuts: image
segmentation (7.10), project selection (7.11).
- Lecture 7. Probability recap (13.12). Randomized algorithms:
Repeating a random experiment. Global Min-Cut (13.2).
- Lecture 8. Max-3-Sat (13.4). XP and FPT. Small vertex covers (10.1).
- Lecture 9. Dynamic programming on subsets. Color coding.
- Lecture 10. Dynamic programming on trees (10.2). Analysis of random
- Lecture 11. Chernoff bounds with an application to load
balancing (13.9-13.10). Verifying matrix products.
- Lecture 12. Hashing and finding closest points (13.6-13.7).
Typos, Clarifications, etc.
Lecture 1, page 3, line -4: The second sum ends with n rather than m.
Large parts of the course are based on selected sections from the book
Jon Kleinberg, Eva Tardos: Algorithm Design.
However, some contents may come from various other materials, i.e., they are
not in the book. It should be possible to follow the course using the Lecture
Notes only, but the book may serve as supplementary material.
See also the course plan. After the course you should
- know in more depth some important design and analysis techniques for
algorithms, in particular, ways to approach NP-complete problems,
- to some extent be able to apply such techniques to solve new problems
that may arise in various applications,
- have some practice in recognizing connections between algorithmic problems
and reducing them to each other,
- be able to explain more complex algorithms and proofs in written form,
- know selected topics of current research on algorithms.
Grading is based on compulsory assignments and a home exam that
have equal weight. The assignments are usual problem solving exercises. In the
home exam you also get some specific algorithmic problem, but it can be treated
in a more essayistic form. The report will be evaluated based on depth, factual
correctness, and clarity of presentation. The detailed exam problem(s) and
instructions are posted in December, and the submission deadline is in the exam
period in January.
The previous exam from
2019 may give
We do not use any point system, but we record the feedback comments and apply
the following grading criteria.
5/VG: Your solutions are correct; they really solve the given problems;
they are presented in a logical order and can be followed step by step; all
these steps are conclusive; all claims are weil motivated; notations are well
defined. There are at most some minor weak points.
4/G: Your submissions mainly fulfill the above criteria, but there also
remain noticeable errors, difficulties, or gaps.
3/G: You show a basic understanding of the topics and can manage most
problems, however with substantial difficulties.
U: Insufficient understanding and fundamental difficulties in most
Thus, not all exercises need to be "OK'd" in order to pass the course, but
omissions can lower your grade. Feel free to ask at any time what grade you
can expect based on the solutions shown so far.
There is no scheduled re-exam, but you as a Chalmers student can improve your
grade later on by follow-up assignments. (Be aware that this is not merely a
formality. You must really achieve an improvement that justifies the higher
grade.) You can express your interest before a certain deadline, and the
assignment should be finished before another deadline (to be announced).
GU students do not have this possibility, according to GU regulations.
Rules and Policies
Read them carefully and take them very seriously.
- Exercise deadlines are firm. Delays must be motivated before the
deadlines. Unannounced late submissions will not be considered. Once you have
submitted a first version before the deadline, you are allowed to resubmit at
- It is allowed, even encouraged, to discuss the exercises during the course. Also, do not hesitate to ask if you have difficulties with the
exercises, or if something is unclear.
- However, you must write your final solutions on your own, using your own
words, and expressing them in the way you understood them yourself.
- Submitting others' work in your own name is cheating! It can lead
to severe consequences, in very bad cases even suspension from studies.
- Specifically, it is prohibited to copy (with or without modifications)
from each other, from books, articles, web pages, etc., and to submit solutions that you got from external persons. All sources beyond the course materials
must be explicitly acknowledged.
- You are also responsible for not giving others the opportunity to cheat.
We will not investigate who copied from whom.
We do not use the Assignments feature of Canvas, but everything is done simply
by mail. This system (or rather non-system) has proved, over the years, to be
well suited for the pedagogical goals of this course, as it is most flexible.
Further remarks: Clear technical writing, besides solving the problems, is an
important aspect of the assignments. Slight formulation details can make a difference: Even if two authors had the same solution in mind, one write-up can
be comprehensible and the other one not. If you think that some comments are
wrong or based on misunderstandings (we are not free of mistakes!), do not
hesitate to discuss your doubts. Anyway, this is part of the resubmission
- When you describe an algorithm: Explain how and why it works, do not only
provide uncommented pseudocode.
- Be concise, avoid unnecessary additional writing. In particular, you need
not prove facts that are already known from the course.
- Respect the deadlines (see Rules and Policies). It is strongly recommended
to start working when the exercises have been posted, not only when the
deadline is approaching.
- Solutions must be submitted individually (not in groups!) by email
to "ptr..." The subject line must contain the course code and exercise numbers.
- Please send only PDF attachments, no other formats. Submitting
handwritten and scanned solutions is not encouraged, but if you do so, the PDF
must be legible.
- Send the entire assignment as one document, rather than a separate
file for each exercise.
- Write your name, personal number, and email address in the PDF (not
only in the mail).
- If you could not solve an exercise, submit anyway and point out precisely
where you got stuck. This may help us give further hints. An even better way is
to ask for help early.
- If you get feedback on an exercise: Improve your solution
accordingly and resubmit as soon as possible.
- Please resubmit the complete solution, not only isolated answers. (It can
be hard to trace them.) Moreover, it helps us if you mark the changes.
- There is no fixed limit on the number of resubmissions. However, try and
address all comments, in order to avoid long chains of incremental
- No resubmission deadlines are set during the course. There will be only
one final deadline for all resubmissions.