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Parameterized Complexity NewsNewsletter of the Parameterized Complexity Community Vol 13, No 3. October 2017ISSN 2203109X


Editors Frances Rosamond (Univ Bergen)

and Valia Mitsou (Univ Paris Diderot)

Congratulations to all for many awards and prizes,graduates, new jobs, and wonderful research. ALGO 2017showcased ten awards and 8 of them were related to pa-rameterized complexity! This newsletter includes articlesby the IPEC Best Paper and Excellent Student PaperAward winners. Articles by PACE winners will be fea-tured in the January 2018 newsletter. See ALGO photoson Mikes facebook page @MikeFellowsFPT.

2017 Nerode Prize Congratulations!

The EATCS-IPEC Nerode Prize 2017 for outstanding pa-pers in multivariate algorithmics has been awarded to Fe-dor Fomin (Univ Bergen), Fabrizio Grandoni (IDSIA,Univ Lugano), and Dieter Kratsch (Univ Lorraine-Metz) for: A measure and conquer approach for the anal-ysis of exact algorithms (JACM 65 (5): Article 25, 2009).

Sullivan awarded US Army Grant

Dr. Blair Sullivan, Associate Professor of Computer Sci-ence at NC State University, has been awarded $538,199by the US Army Research Office to support her FPT ori-ented research proposal: Algorithms for Exploiting Ap-proximate Network Structure. Erik Demaine (MIT) is co-PI. The award will run from 2017 - 2020.

Figure 1: Dr. Blair Sullivan, US Army grant winner.

Figure 2: Prof Gregory Gutin, M.A.E.

Gregory Gutin to Academia Europaea

Congratulations to Gregory Gutin (Professor of Com-puter Science, Royal Holloway, University of London),

Contents of this issue:Welcome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1Fomin, Grandoni, Kratsch win Nerode Prize . . . . . 1Sullivan awarded US Army Grant . . . . . . . . . . . . . . . 1Gregory Gutin to Academia Europaea . . . . . . . . . . . 1Stewart and Paulusma win EPSRC . . . . . . . . . . . . . . 2Pieterse, Jansen - IPEC Excellent Student Paper 2Curticapean, Dell, Fomin, Goldberg, Lapinskas-IPEC Best Paper Award . . . . . . . . . . . . . . . . . . . . . . . . 2Tamaki-ESA Track B Best Paper . . . . . . . . . . . . . . . . 2Bentert, van Bevern, Nichterlein, Niedermeier-ALGOSENSORS Best Paper . . . . . . . . . . . . . . . . . . . . 2Roth wins ESA Best Student Paper Award . . . . . . 2Cygan, Kowalik, Socala-ESA Track A Best Paper2

Bentert, Fluschnik, Nichterlein, Niedermeier-FCTBest Student Paper . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2Aleksandrov, Walsh-KI Best Paper Award . . . . . . . 2PACE17 Experiments Challenge winners . . . . . . . . 2Jansen and Pieterse: Optimal Data Reduction forGraph Coloring Using Low-Degree Polynomials . . 3Radu Curticapean et al: Fixed-parameter #BIS . 5IPEC 2017 Business Meeting . . . . . . . . . . . . . . . . . . . . 6Conferences and Workshops . . . . . . . . . . . . . . . . . . . . . 6Moving Around . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7Congratulations New PhDs . . . . . . . . . . . . . . . . . . . . . . 7Welcome New FPTers . . . . . . . . . . . . . . . . . . . . . . . . . . . 8PACE Award Ceremony . . . . . . . . . . . . . . . . . . . . . . . . . 8


Parameterized Complexity News 2

who has been elected to the Academia Europaea as aMember of the Informatics Section. See

Stewart and Paulusma win EPSRC

Congratulations to Iain Stewart and DanielPaulusma (Durham Univ), who have won an EP-SRC grant for ALGOUK - a network of six UK univ(Durham, Kings College London, Royal Holloway, Liver-pool, Leicester, Warwick), for 3 years (100K). ALGOUKwill fund a range of activities to bring together researcherson algorithms in the UK and facilitate interactions withresearchers in other disciplines and industry.

Pieterse and Jansen win IPEC ExcellentStudent Paper Award

Congratulations to Astrid Pieterse and Bart M. P.Jansen (Eindhoven Univ of Technology) for winning theIPEC 2017 Excellent Student Paper Award for OptimalData Reduction for Graph Coloring Using Low-DegreePolynomials. A summary follows in this newsletter.

Figure 3: IPEC 2017 Excellent Student Paper Award win-ners Bart Jansen and Astrid Pieterse.

Curticapean, Dell, Fomin, Goldberg, Lap-inskas win IPEC Best Paper Award

Congratulations to Radu Curticapean (HungarianAcademy of Sciences), Holger Dell (Saarland Univ),Fedor Fomin (Univ Bergen), Leslie Ann Goldberg(Univ Oxford) and John Lapinskas (Univ Oxford), whohave won IPEC 2017 Best Paper Award for A Fixed-Parameter Perspective on #BIS. See following summary.

Tamaki wins ESA Track B Best Paper

Congratulations to Hisao Tamaki (Meiji Univ), who haswon ESA 2017 Track B Best Paper Award for his pa-per accompanying his PACE 2017 submission, Positive-instance driven dynamic programming for treewidth. Hesays this work would not have happened without the mo-tivation of the PACE challenge. Hisaos research will beshowcased in the January 2018 Newsletter.

Bentert, van Bevern, Nichterlein, Nieder-meier win ALGOSENSORS Best Paper

Congratulations to Matthias Bentert, Rene van Bev-ern, Andre Nichterlein, Rolf Niedermeier, for win-ning ALGOSENSORS Best Paper Award, AlgorithmsTrack for Parameterized algorithms for power-efficientconnected symmetric wireless sensor networks.

Roth wins ESA Best Student Paper Award

Congratulations to Marc Roth (Saarland Univ), whohas won ESA 2017 Best Student Paper Award for Count-ing restricted homomorphisms via Mobius inversion overmatroid lattices.

Cygan, Kowalik, Socala win ESA Track ABest Paper Award

Congratulations to Marek Cygan, Lukasz Kowalik,Arkadiusz Socala (Univ Warsaw), for winning ESA2017 Track A Best Paper Award for Improving TSP toursusing dynamic programming over tree decompositions.

Bentert, Fluschnik, Nichterlein, Nieder-meier win FCT Best Student Paper

Congratulations to Matthias Bentert, Till Fluschnik,Andre Nichterlein, Rolf Niedermeier for winningBest Student Paper Award at the 21st Symposium onFundamentals of Computation Theory (FCT 17) for Pa-rameterized Aspects of Triangle Enumeration.

Aleksandrov, Walsh win at KI2017

Congratulations to Martin Aleksandrov and TobyWalsh for Expected Outcomes and Manipulations inOnline Fair Division, which won Best Paper Prize atthe 40th German Conference on Artificial Intelligence(KI2017). This is the second time Martin has won abest paper award during his PhD.

PACE17 Experiments Challenge winners


1. Lukas Larisch (King-Abdullah Univ Science andEngineering), Felix Salfelder (Univ Leeds)

2. Hiromu Ohtsuka, Hisao Tamaki (Meiji Univ)3. Max Bannach (Univ Lubeck), Sebastian

Berndt (Univ Lubeck), Thorsten Ehlers (UnivKiel)


1. Keitaro Makii, Hiromu Ohtsuka, TakutoSato, Hisao Tamaki (Meiji Univ)

2. Ben Strasser (Karlsruhe Institute of Technology)

Parameterized Complexity News 3

Figure 4: PACE 2017 Award Winners

3. Michael Abseher, Nysret Musliu, StefanWoltran (TU Wien)


4. Max Bannach (Univ Lubeck), SebastianBerndt (Univ Lubeck), Thorsten Ehlers (UnivKiel)

5. Philippe Jegou, Hanan Kanso, Cyril Terrioux(Aix-Marseille Universite, LSIS)

6. Lukas Larisch (King-Abdullah Univ Science andEngineering), Felix Salfelder (Univ Leeds)


1. Yasuaki Kobayashi (Kyoto Univ), HisaoTamaki (Meiji Univ)

2. Jeremias Berg, Matti Jarvisalo, Tuukka Ko-rhonen (Univ Helsinki)

3. Edouard Bonnet (UnivParis-Dauphine), R.B.Sandeep (Hungarian Academy of Sciences), Flo-rian Sikora (Univ Paris-Dauphine)


4. Anders Wind Steffensen, Mikael Lindemann(IT Univ Copenhagen)

5. Kaustubh Joglekar, Akshay Kamble, RajeshPandian (Indian Institute Of Technology, Madras)

6. Saket Saurabh (Univ Bergen), PrafullkumarTale (Institute of Mathematical Sciences, Chennai)

7. Mani Ghahremani (Univ Portsmouth)8. Frederik Madsen, Mikkel Gaub, Malthe

Kirkbro (IT Univ Copenhagen)

Congratulations to Parameterized AlgorithmsComputational Experiments (PACE 2017) win-ning teams and participants. See for a list of papers re-sulting from PACE. Read about winning strategies inThe PACE 2017 Parameterized Algorithms and Compu-tational Experiments Challenge: The Second Iteration(IPEC 2017 Proceedings). The libraries developed willbe useful for Masters projects. Let us know how you usethe results. Some instances were real-world transit androad graphs submitted by Johannes Fichte (TU Wien)and Ben Strasser (Karlsruhe Institute of Technology).

The 2018 Steering Committee Chair for PACE is BartJansen (Eindhoven Univ of Technology). The PACE2018 PCs are Edouard Bonnet and Florian Sikora,both at Univ Paris-Dauphine. Huge thanks to the PCswho have done so much during the 2016 and 2017 chal-lenges: Track A: Holger Dell (Saarland Univ), TrackB: Christian Komusiewicz (Chair) (Friedrich-Schiller-Univ Jena), Nimrod Talmon (Weizmann Institute ofScience), Mathias Weller (Lab of Informatics, Robotics,and Microelectronics of Montpellier (LIRMM)).

Grateful appreciation goes to the NWO GravitationProject Networks, our PACE sponsor. Photos, thanksto Rudolf Fleischer (GUtech), are on facebook @Mike-FellowsFPT, and at ALGO Gallery and Dropbox. ThePACE Award Ceremony was fun with prizes courtesy ofFrances Rosamond (Univ Bergen). Sign up for thePACE Newsletter and join the 2018 Steiner Tree Chal-lenge at http://pacechallenge.wordpress.comp.

Parameterized Complexity News 4

Optimal Data Reduction for Graph Color-ing Using Low-Degree Polynomials

by Astrid Pieterse (Eindhoven Univ of Technology, NL)

This short article summarizes the main algorithmicidea in the IPEC 2017 Best Student Paper Award paperby Bart M. P. Jansen and Astrid Pieterse [2].

Introduction The q-Coloring problem, askingwhether the vertices of a graph can be properly coloredusing at most q different colors, has been widely studied.Since, even 3-Coloring is NP-hard, the number of col-ors is not a suitable parameter and the problem has beenstudied using several structural parameters. Jansen andKratsch [1] studied the problem for a hierarchy of differentparameters. One of their results was that q-Coloringparameterized by the size of a Vertex Cover in thegraph has a kernel of bitsize O(kq). Furthermore, theyshowed for q 4 that it has no kernel of size O(kq1),unless NP coNP/poly. This left a factor-k gap betweenthe upper and lower bound, and it was not clear whichcould be strengthened. We show that q-Coloring pa-rameterized by Vertex Cover has a kernel withO(kq1) vertices and bitsize O(kq1 log k), thereby clos-ing the gap between the upper and lower bound up toko(1) factors.

In previous work [4], the current authors showed forq 4, that the q-Coloring problem with n verticeshas no kernel of size O(n2), unless NP coNP/poly.It remained unclear whether the same was true for 3-Coloring. One might think that dense graphs are ei-ther not 3-colorable, or have very specific structure. Thiscould then be exploited to find a better kernel. How-ever, we show in the paper [2] that 3-Coloring has nokernel of size O(n2), strengthening our previous result.This also implies that 3-Coloring parameterized byVertex Cover has no kernel of size O(k2), under thesame assumption. Together with the known lower boundby Jansen and Kratsch [1], this shows that q-Coloringparameterized by Vertex Cover has no kernel ofsize O(kq1) for q 3, unless NP coNP/poly.

Kernelization In this summary, we will show how toobtain a kernel of bitsize O(kq1 log k) for q-Coloringparameterized by Vertex Cover. Consider inputgraph G with vertex cover vc. The remaining verticesform independent set is. The challenge is that is may belarge compared to the size of the vertex cover. To obtaina kernel, we will find vertices in v is, such that any col-oring of G v can be extended to color the entire graph.We call such vertices redundant.

The kernel is based on the observation that each ver-tex v is poses a constraint on its neighborhood, namelythat The neighborhood of v should not use all q colors.Equivalently, for each vertex v is, for each S N(v)with |S| = q, we require that Some color is used twice inS. Note that this is equivalent to saying that S leavessome color unused, by the size of S. If some coloring of vc

satisfies all(|N(v)|


)constraints corresponding to v is,

it is easy to see that this coloring can be extended to v.We will now find redundant vertices, by replacing all ver-tices in is by constraints. This gives a set of constraintsL. Then we find a subset L L of relevant constraints.This subset is chosen such that any coloring satisfying theconstraints in L, must satisfy all original constraints.

The problem now boils down to finding a small set ofrelevant constraints. For this, we use a technique thatwe introduced in previous work [3]. There, we give apolynomial-time algorithm that does the following: Givena set L of polynomial equalities of degree at most d overn boolean variables, it outputs L L with |L| nd + 1such that any boolean assignment satisfying all equalitiesin L, satisfies L. In particular, this technique works whengiven equalities over the integers modulo 2. All that isneeded to obtain L is to form a linear system over anextended set of variables: there is one meta-variable foreach monomial. A constraint then translates into a lin-ear equality on these meta-variables, and L can be foundby computing a basis of the associated extended linearsystem using Gaussian elimination.

In order to use the above result, we must model theconstraints as a set of polynomial equalities over booleanvariables. First of all, create q boolean variables for eachvertex in vc, and label them yv,k for v vc and k [q].To describe the color of a vertex, let yv,k = 1 if vertex vhas color k, and zero otherwise. It remains to replace theconstraint these q vertices use at least one color twiceby a low-degree polynomial equality. Let S vc with|S| = q be the considered set of vertices. Then we use thefollowing polynomial equality of degree q 1:




yvk,k 0 (mod 2).

For q = 3 and S = {u...


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