Complexity and computability once again.
Bloom filters.
Data structures.
Data structures and what we would expect on the exam.
Hash functions.
State holiday.
Moved mentoring. Data structures.
No mentoring today. Ask your questions using email.
Morning session in our office.
Data structures questions.
Data structures questions.
Splay trees measurements.
Plotting data.
Splay trees (beware there are some nice pictures but also some terrible mistakes on Wikipedia).
Rotations on Splay trees -- why single rotations are not enough.
Splay trees can be linearly deep!
Software project try announcing your software project at some facebook group or in the classroom.
Email questions and advertisement during classes.
Approximation algorithms. Scheduling and metric travelling salesman.
Complexity, big O notation. Working with memory in C++.
Reductions again but for a different audience.
Reductions.
Hierarchy theorems with construction of universal turing machine. Four diagonalization proofs (size of the set of real numbers and natural numbers, set theory, computability, complexity -- hierarchy theorems).
We are making an unofficial preparatory course for Data Structures. You should get an email about this, if you have not send me and email and I will add you to the mail list. If you want to participate implement a linked list and sorting using linked list.
We are starting the Data Structures 101 minicourse (I will send an email about it).
Time and space complexity, big O notation, deterministic vs nondeterministic Turing machines, P vs NP (without proof).
We need to leave early, please meet us in our office at 13:00. We need to leave by 15:00 (preferably earlier). We are happy to answer your emails during the weekend or meet you during next week.
Space and time complexity, intuition, relations with each other, complexity classes.
If you are interested we are able to do a Programming and Data Structures 101 course. Ideally during this semester, the sooner the better. (We are tutors for czech students for Datastructures I course.)
Post Correspondence Theorem and reducibility of problems.
Reducibility, completeness, hardness. Mainly for complexity theory (with introduction of non-deterministic machines and the class NP).
Computability theory, Gödel enumeration of Turing machines, diagonalization, halting problem and intuition behind all this.
There were just four students. You can meet us this Friday 14:00 in our office, fifth floor, ring the bell "Doktorandi KAM". We will also be in the room S4 at 15:40 for limited time, if someone comes.
Book on computability: pretty much slide 4 from the lecture., Arora Barak is available for free in pdf. Two other books (I have not read those, but both seem nice, the books might be written from another point of view, so I cannot tell how useful those are for the classes) http://computingbook.org/ http://hjemmesider.diku.dk/~neil/comp2book2007/book-whole.pdf
Libraries: MFF UK library catalog. National Library of Technology (you might need to pay a reasonable membership fee). Municipal Library of Prague (general purpose, again you need to pay some fee).
Student licence for software: you may try to use computers in the computer lab. List of available software (mainly in czech, but do not hesitate to use an online translator or to ask us for a translation).
Introduction of each other.
Signing up for classes.
Software project and Thesis.
A: Ke Karlovu 3, go there, be nice, they will help you.
A: Yes, these will be counted as optional credits (not compulsory and also not elective).
A: Adam Dingle will give an overview Friday 12.10 from 15:40 - 16:40 in room S11.
A: See this site. We will happily add more info in case anyone is interested.
A: We can make this happen or give you enough material.
A: An awesome visual math tutorials 3blue1brown. Check this out!
A: No! You only need to get 45 credits by the end of semester. Take a look at this study guide page.
A: You should get at least 45 credits each year. This is the bare minimum (you should optimally get at least 60 credits).
A: Yes! Sometimes even in english! See for instance the very popular course of Deep learning by Milan Straka!