54 research outputs found
Approximate Counting of k-Paths: Deterministic and in Polynomial Space
A few years ago, Alon et al. [ISMB 2008] gave a simple randomized O((2e)^km epsilon^{-2})-time exponential-space algorithm to approximately compute the number of paths on k vertices in a graph G up to a multiplicative error of 1 +/- epsilon. Shortly afterwards, Alon and Gutner [IWPEC 2009, TALG 2010] gave a deterministic exponential-space algorithm with running time (2e)^{k+O(log^3k)}m log n whenever epsilon^{-1}=k^{O(1)}. Recently, Brand et al. [STOC 2018] provided a speed-up at the cost of reintroducing randomization. Specifically, they gave a randomized O(4^km epsilon^{-2})-time exponential-space algorithm. In this article, we revisit the algorithm by Alon and Gutner. We modify the foundation of their work, and with a novel twist, obtain the following results.
- We present a deterministic 4^{k+O(sqrt{k}(log^2k+log^2 epsilon^{-1}))}m log n-time polynomial-space algorithm. This matches the running time of the best known deterministic polynomial-space algorithm for deciding whether a given graph G has a path on k vertices.
- Additionally, we present a randomized 4^{k+O(log k(log k + log epsilon^{-1}))}m log n-time polynomial-space algorithm. While Brand et al. make non-trivial use of exterior algebra, our algorithm is very simple; we only make elementary use of the probabilistic method.
Thus, the algorithm by Brand et al. runs in time 4^{k+o(k)}m whenever epsilon^{-1}=2^{o(k)}, while our deterministic and randomized algorithms run in time 4^{k+o(k)}m log n whenever epsilon^{-1}=2^{o(k^{1/4})} and epsilon^{-1}=2^{o(k/(log k))}, respectively. Prior to our work, no 2^{O(k)}n^{O(1)}-time polynomial-space algorithm was known. Additionally, our approach is embeddable in the classic framework of divide-and-color, hence it immediately extends to approximate counting of graphs of bounded treewidth; in comparison, Brand et al. note that their approach is limited to graphs of bounded pathwidth
Algebraic Methods in the Congested Clique
In this work, we use algebraic methods for studying distance computation and
subgraph detection tasks in the congested clique model. Specifically, we adapt
parallel matrix multiplication implementations to the congested clique,
obtaining an round matrix multiplication algorithm, where
is the exponent of matrix multiplication. In conjunction
with known techniques from centralised algorithmics, this gives significant
improvements over previous best upper bounds in the congested clique model. The
highlight results include:
-- triangle and 4-cycle counting in rounds, improving upon the
triangle detection algorithm of Dolev et al. [DISC 2012],
-- a -approximation of all-pairs shortest paths in
rounds, improving upon the -round -approximation algorithm of Nanongkai [STOC 2014], and
-- computing the girth in rounds, which is the first
non-trivial solution in this model.
In addition, we present a novel constant-round combinatorial algorithm for
detecting 4-cycles.Comment: This is work is a merger of arxiv:1412.2109 and arxiv:1412.266
Graph and Hypergraph Decompositions for Exact Algorithms
This thesis studies exact exponential and fixed-parameter algorithms for hard graph and hypergraph problems. Specifically, we study two techniques that can be used in the development of such algorithms: (i) combinatorial decompositions of both the input instance and the solution, and (ii) evaluation of multilinear forms over semirings.
In the first part of the thesis we develop new algorithms for graph and hypergraph problems based on techniques (i) and (ii). While these techniques are independently both useful, the work presented in this part is largely characterised by their joint application. That is, combining results from different pieces of the decompositions often takes the from of multilinear form evaluation task, and on the other hand, decompositions offer the basic structure for dynamic-programming-style algorithms for the evaluation of multilinear forms.
As main positive results of the first part, we give algorithms for three different problem families. First, we give a fast evaluation algorithm for linear forms defined by a disjointness matrix of small sets. This can be applied to obtain faster algorithms for counting maximum-weight objects of small size, such as k-paths in graphs. Second, we give a general framework for exponential-time algorithms for finding maximum-weight subgraphs of bounded tree-width, based on the theory of tree decompositions. Besides basic combinatorial problems, this framework has applications in learning Bayesian network structures. Third, we give a fixed-parameter algorithm for finding unbalanced vertex cuts, that is, vertex cuts that separate a small number of vertices from the rest of the graph.
In the second part of the thesis we consider aspects of the complexity theory of linear forms over semirings, in order to better understand technique (ii). Specifically, we study how the presence of different algebraic catalysts in the ground semiring affects the complexity. As the main result, we show that there are linear forms that are easy to compute over semirings with idempotent addition, but difficult to compute over rings, unless the strong exponential time hypothesis fails.Yksi tietojenkĂ€sittelytieteen perustavista tavoitteista on tehokkaiden algoritmien kehittĂ€minen. Teoreettisesta nĂ€kökulmasta algoritmia yleensĂ€ pidetÀÀn tehokkaana mikĂ€li sen ajoaika riippuu polynomisesti syötteen koosta. On kuitenkin laskennallisia ongelmia, joihin ei ole olemassa polynomiaikaisia algoritmeja. Esimerkiksi NP-kovia ongelmia ei voi ratkaista polynomisessa ajassa, mikĂ€li yleinen vaativuusolettamus P â NP pitÀÀ paikkansa. TĂ€stĂ€ huolimatta haluaisimme kuitenkin usein ratkaista tĂ€llaisia vaikeita ongelmia.
Kaksi yleistÀ lÀhestymistapaa vaikeiden, polynomisessa ajassa ratkeamattomien ongelmien tarkkaan ratkaisemiseen on (i) eksponentiaalinen algoritmiikka ja (ii) parametrisoitu algoritmiikka. Eksponentiaaliaikaisessa algoritmiikassa kehitetÀÀn algoritmeja, joiden ajoaika on edelleen eksponentiaalinen syötteen koon suhteen, mutta jotka vÀlttÀvÀt koko ratkaisuavaruuden lÀpikÀynnin; toisin sanoen, kyse on vÀhemmÀn eksponentiaalisten algoritmien kehittÀmisestÀ. Parametrisoitu algoritmiikka puolestaan pyrkii eristÀmÀÀn eksponentiaaliaikaisen riippuvuuden ajoajassa syötteen koosta riippumattomaan parametriin.
TÀssÀ vÀitöstyössÀ esitetÀÀn eksponentiaaliaikaisia ja parametrisoituja algoritmeja erinÀisten vaikeiden verkko- ja hyperverkko-ongelmien tarkkaan ratkaisemiseen. Esitetyt algoritmit perustuvat kahteen algoritmiseen tekniikkaan: (i) monilineaarimuotojen evaluoiminen yli erilaisten puolirengaiden ja (ii) kombinatoristen hajotelmien kÀyttö. Algoritmien lisÀksi työssÀ tarkastellaan nÀihin tekniikoihin liittyviÀ vaativuusteoreettisia kysymyksiÀ, mikÀ auttaa ymmÀrtÀmÀÀn tekniikoiden rajoituksia ja toistaiseksi hyödyntÀmÀttömiÀ mahdollisuuksia
Homomorphisms are a good basis for counting small subgraphs
We introduce graph motif parameters, a class of graph parameters that depend
only on the frequencies of constant-size induced subgraphs. Classical works by
Lov\'asz show that many interesting quantities have this form, including, for
fixed graphs , the number of -copies (induced or not) in an input graph
, and the number of homomorphisms from to .
Using the framework of graph motif parameters, we obtain faster algorithms
for counting subgraph copies of fixed graphs in host graphs : For graphs
on edges, we show how to count subgraph copies of in time
by a surprisingly simple algorithm. This
improves upon previously known running times, such as time
for -edge matchings or time for -cycles.
Furthermore, we prove a general complexity dichotomy for evaluating graph
motif parameters: Given a class of such parameters, we consider
the problem of evaluating on input graphs , parameterized
by the number of induced subgraphs that depends upon. For every recursively
enumerable class , we prove the above problem to be either FPT or
#W[1]-hard, with an explicit dichotomy criterion. This allows us to recover
known dichotomies for counting subgraphs, induced subgraphs, and homomorphisms
in a uniform and simplified way, together with improved lower bounds.
Finally, we extend graph motif parameters to colored subgraphs and prove a
complexity trichotomy: For vertex-colored graphs and , where is from
a fixed class , we want to count color-preserving -copies in
. We show that this problem is either polynomial-time solvable or FPT or
#W[1]-hard, and that the FPT cases indeed need FPT time under reasonable
assumptions.Comment: An extended abstract of this paper appears at STOC 201
Discrete Geometry
The workshop on Discrete Geometry was attended by 53 participants, many of them young researchers. In 13 survey talks an overview of recent developments in Discrete Geometry was given. These talks were supplemented by 16 shorter talks in the afternoon, an open problem session and two special sessions. Mathematics Subject Classification (2000): 52Cxx. Abstract regular polytopes: recent developments. (Peter McMullen) Counting crossing-free configurations in the plane. (Micha Sharir) Geometry in additive combinatorics. (JoÌzsef Solymosi) Rigid components: geometric problems, combinatorial solutions. (Ileana Streinu) âą Forbidden patterns. (JaÌnos Pach) âą Projected polytopes, Gale diagrams, and polyhedral surfaces. (GuÌnter M. Ziegler) âą What is known about unit cubes? (Chuanming Zong) There were 16 shorter talks in the afternoon, an open problem session chaired by JesuÌs De Loera, and two special sessions: on geometric transversal theory (organized by Eli Goodman) and on a new release of the geometric software Cinderella (JuÌrgen Richter-Gebert). On the one hand, the contributions witnessed the progress the field provided in recent years, on the other hand, they also showed how many basic (and seemingly simple) questions are still far from being resolved. The program left enough time to use the stimulating atmosphere of the Oberwolfach facilities for fruitful interaction between the participants
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