IGAFIT Algorithmic Colloquium

We are excited to announce a new online seminar - IGAFIT Algorithmic Colloquium. This new event aims to integrate the European algorithmic community and keep it connected during the times of the pandemic. This online seminar will take place biweekly on Thursday at 14:00 CET, with the talks lasting for 45 minutes. Each talk will be followed by a networking and discussion session on topics related to the talk. We cordially invite all participants to this session. The meeting will be run on Airmeet. More details on the event can be found on IGAFIT web page.

The first talk will be held on the 1st of October 2020.

October 1, 2020
Vera Traub, University of Bonn
Title: An improved approximation algorithm for ATSP
Abstract: In a recent breakthrough, Svensson, Tarnawski, and Végh gave the first constant-factor approximation algorithm for the asymmetric traveling salesman problem (ATSP). In this work we revisit their algorithm. While following their overall framework, we improve on each part of it.

Svensson, Tarnawski, and Végh perform several steps of reducing ATSP to more and more structured instances. We avoid one of their reduction steps (to irreducible instances) and thus obtain a simpler and much better reduction to vertebrate pairs. Moreover, we show that a slight variant of their algorithm for vertebrate pairs has a much smaller approximation ratio.

Overall we improve the approximation ratio from 506 to 22 + ε for any ε > 0. We also improve the upper bound on the integrality ratio of the standard LP relaxation from 319 to 22.

This is joint work with Jens Vygen.

Other upcoming talks include:

October 15, 2020
Thatchaphol Saranurak, Toyota Technological Institute at Chicago
Title: An almost-linear time deterministic algorithm for expander decomposition

October 29, 2020
Nathan Klein, University of Bonn
Title: A (Slightly) Improved Approximation Algorithm for Metric TSP

For more details please contact the Organization Committee:
Nikhil Bansal
Artur Czumaj
Andreas Feldmann
Adi Rosén
Eva Rotenberg
Piotr Sankowski
Christian Sohler 

Faster PageRank on MPC

Years ago when I learned about Google PageRank algorithm, my first reaction was this is not the way it should be done! There should be some proof. This probably just shows that my CS education was too theoretical ;). Years later I have learned that indeed there are some nice tools to argue about the running time of PageRank algorithm. And very recently we were able to give some new parallel (in MPC model) algorithms for computing vanilla PageRank. We improved the number of rounds needed from O(log n) to O(log^2 log n) time. You can hear Solbodan talking out it here: https://www.youtube.com/watch?v=xoodhmjJ9Xs .

We are looking for YOU to join our award-winning scientific team!

Have you just graduated your PhD and are considering a post-doc position in theory of informatics? Science is your passion and you would like to spend most of your post-doc researching on whatever interests you? You are in the right place.

At MIM UW we offer you:

  1. Great FREEDOM OF CHOICE related to what to work on;
  2. Just A FEW or NO teaching duties;
  3. A lot of TIME FOR RESEARCH;
  4. Chance to cooperate with VERY EXPERIENCED and TALENTED scientists;
  5. FRIENDLY environment;
  6. Excellent SUPPORT from our administrative staff;

If you still hesitate, here are two interviews with former post-docs in ERC GRANT TUgbOAT.

Watch a video and find out more about benefits of working at MIM UW.

Watch an interview with Krzysztof Fleszar, post-doc at the Faculty of Mathematics, Informatics and Mechanics, University of Warsaw and find out how the participation in the project has changed his life.
For more information about ERC GRANT TUgbOAT visit our blog https://duch.mimuw.edu.pl/~tugboat/.
Adam Karczmarz told us about his experience as a post-doc at the Faculty of Mathematics, Informatics and Mechanics, University of Warsaw in ERC GRANT „Towards Unification of Algorithmic Tools”.
To find out more about TUgbOAT project visit our blog https://duch.mimuw.edu.pl/~tugboat/.

Call for Invited Talk Nominations: HALG 2020

5th Highlights of Algorithms conference (HALG 2020)

ETH Zurich, June 3-5, 2020


The HALG 2020 conference seeks high-quality nominations for invited talks that will highlight recent advances in algorithmic research. Similarly to previous years, there are two categories of invited talks:

A. survey (60 minutes): a survey of an algorithmic topic that has seen exciting developments in last couple of years.

B. paper (30 minutes): a significant algorithmic result appearing in a paper in 2019 or later.

To nominate, please email halg2020.nominations@gmail.com the following information:

  1. Basic details: speaker name + topic (for survey talk) or paper’s title, authors, conference/arxiv + preferable speaker (for paper talk).
  2. Brief justification: Focus on the benefits to the audience, e.g., quality of results, importance/relevance of topic, clarity of talk, speaker’s presentation skills.

All nominations will be reviewed by the Program Committee (PC) to select speakers that will be invited to the conference.

Nominations deadline: December 20, 2020 (for full consideration).

Call for Participation: HALG 2019 (Highlights of Algorithms)

4rd Highlights of Algorithms conference (HALG 2019)
Copenhagen, June 14-16, 2019

The Highlights of Algorithms conference is a forum for presenting the
highlights of recent developments in algorithms and for discussing
potential further advances in this area. The conference will provide a
broad picture of the latest research in algorithms through a series of
invited talks, as well as the possibility for all researchers and
students to present their recent results through a series of short
talks and poster presentations. Attending the Highlights of Algorithms
conference will also be an opportunity for networking and meeting
leading researchers in algorithms.


The conference will begin on Friday, June 14, at 9:00 and end on
Sunday, June 16, at 18:00. A detailed schedule and a list of all
accepted short contributions can be found at:



Please register on our webpage
We have done our best to keep registration fees at a minimum:

Early registration (by April 29, 2019)
- academic rate (incl. postdocs): 160€
- student rate: 115€

Regular registration will be 50€ more expensive.

The organizers strongly recommend that you book your hotel as soon as possible.



The conference will take place at the H.C. Ørsted Institute of the
University of Copenhagen.
The address is: Universitetsparken 5, DK-2100 Copenhagen.



Survey speakers:
Monika Henzinger (University of Vienna)
Thomas Vidick (California Institute of Technology)
Laszlo Vegh (London School of Economics)
James Lee (University of Washington)
Timothy Chan (University of Illinois at Urbana-Champaign)
Sergei Vassilvitskii (Google, New York)

Invited talks:
Martin Grohe (RWTH Aachen University)
Josh Alman (MIT)
Nima Anari (Stanford University)
Michal Koucký (Charles University)
Naveen Garg (IIT Delhi)
Vera Traub (University of Bonn)
Rico Zenklusen (ETH Zurich)
Shayan Oveis Gharan (University of Washington)
Greg Bodwin (MIT)
Cliff Stein (Columbia University)
Sungjin Im (University of California at Merced)
C. Seshadhriy (University of California, Santa Cruz)
Shay Moran (Technion)
Bundit Laekhanukit (Shanghai University of Finance and Economics)
Sebastien Bubeck (Microsoft Research, Redmond)
Sushant Sachdeva (University of Toronto)
Kunal Talwar (Google Brain)
Moses Charikar (Stanford University)
Shuichi Hirahara (University of Tokyo)


The Curse of Euclidean Metric: Square Roots

The Curse of Metric Island

The deadline was approaching without mercy and there was, of course, still some polishing to be done for our SODA paper. But then we run into an issue. To make things worse, this issue turned out to be a hard one, a fundamental known open problem in computational geometry. The good thing is, I liked the problem so much that I decided to dedicate it this post. This is the story about the Sum of Square Roots problem and how we bypassed (ignored) it without solving it.

Everything began in the haze of the 70's of the last millennium. It is nebulous who stumbled first upon this enigma. Some say that Ron Graham has discussed the problem in public lectures, some others say that Joseph O'Rourke has posed it as an open question in the American Mathematical Monthly, while some others suspect that the problem had been already hiding in older different formulations. However, it is a historical fact that one shinny/cloudy day, three computer scientists finished polishing a manuscript that became a classical paper known as "Some NP-complete geometric problems". In this paper, Michael Garey, Ron Graham and David Johnson showed the NP-hardness of two important problems in geometric metrics: Steiner Tree and Traveling Salesman. For the Euclidean plane, they showed only NP-hardness as they did not manage to show that these problems are contained in NP. Moreover, they accentuated that we cannot even rule out that the decision version of Euclidean Minimum Spanning Tree is outside of NP. What a seeming paradox given that we can compute such a minimum tree in polynomial time! So, whom did they blame? The short answer: The Euclidean metric. Garey and his coauthors explain that all these problems have a common hidden issue: They rely on comparing Euclidean lengths, that is, they rely on comparing irrational numbers based on square roots. Whereas this task is trivial if we just want to compare two line segments (e.g. by comparing the radicands), the problem starts when we want to compare two polygonal paths. Even assuming rational (or, after scaling, integer) coordinates, this problem translates into a question that is fundamental in computational geometry: Given two lists of integers, a1 ... and b1 ..., can we decide whether "∑ √ai ≥ ∑ √bi" in P? Put into words: Can we efficiently compare two sums of square roots over integers?

Continue reading

HALG 2019 - Call For Submissions of Short Contributed Presentations

The HALG 2019 conference seeks submissions for contributed presentations. Each presentation is expected to consist of a poster and a short talk (an invitation to the poster). There will be no conference proceedings, hence presenting work already published at a different venue or journal (or to be submitted there) is welcome.

If you would like to present your results at HALG 2019, please submit their details the abstract of the talk or the contribution of the poster via EasyChair: https://easychair.org/conferences/?conf=halg2019

The abstract should include (when relevant) information where the results have been published/accepted (e.g., conference), and where they are publicly available (e.g., arXiv). All submissions will be reviewed by the program committee, giving priority to new work not formally published yet, and to papers published in 2018 or later.

Submissions deadline: March 15th, 2019.
Late submissions will be accepted subject to space constraints.

Prophet inequality and auction design

Suppose you want to sell a car and there are 10 agents willing to buy it. You are not sure how much they could pay but for each of them you know a probability distribution of how high the offer will be. For example, a car salon would always pay 10K  but some person might offer 5K or 15K with equal probability. The best you could do is to first negotiate with all of them and then pick the highest bid. Unfortunately, you cannot do so - after seeing each offer you must irrevocably choose either to sell the car or to refuse the offer. What is the best strategy to maximize your revenue in this case?

In turns out that this is a well-studied optimization problem with a simple strategy that guarantees you can (on expectation) earn at least half as much as a hypothetical prophet, who knows all the bids in advance. This result is known as the prophet inequality. What is more surprising, this strategy would work even if you are a car retailer and want to sell five cars. Moreover, you might want to have some constraints, for example you do not want to sell two cars to buyers from the same city, or have multiple kinds of cars with different evaluations, and you can always guarantee an expected revenue comparable to the one of the prophets.

This problem not only exploits beautiful math but also has important applications in internet ad display. Actually, whenever you type a query into a web search engine, the ad system performs this kind of car-selling game with the ad suppliers, who offer different bids for their ad to be displayed to you.

Here is a link to our recent work with new developments in this theory: http://ieee-focs.org/FOCS-2018-Papers/pdfs/59f790.pdf

Michał Włodarczyk