229,836 research outputs found
Testing Small Set Expansion in General Graphs
We consider the problem of testing small set expansion for general graphs. A
graph is a -expander if every subset of volume at most has
conductance at least . Small set expansion has recently received
significant attention due to its close connection to the unique games
conjecture, the local graph partitioning algorithms and locally testable codes.
We give testers with two-sided error and one-sided error in the adjacency
list model that allows degree and neighbor queries to the oracle of the input
graph. The testers take as input an -vertex graph , a volume bound ,
an expansion bound and a distance parameter . For the
two-sided error tester, with probability at least , it accepts the graph
if it is a -expander and rejects the graph if it is -far
from any -expander, where and
. The
query complexity and running time of the tester are
, where is the number of
edges of the graph. For the one-sided error tester, it accepts every
-expander, and with probability at least , rejects every graph
that is -far from -expander, where
and for any . The query
complexity and running time of this tester are
.
We also give a two-sided error tester with smaller gap between and
in the rotation map model that allows (neighbor, index) queries and
degree queries.Comment: 23 pages; STACS 201
Testing Cluster Structure of Graphs
We study the problem of recognizing the cluster structure of a graph in the
framework of property testing in the bounded degree model. Given a parameter
, a -bounded degree graph is defined to be -clusterable, if it can be partitioned into no more than parts, such
that the (inner) conductance of the induced subgraph on each part is at least
and the (outer) conductance of each part is at most
, where depends only on . Our main
result is a sublinear algorithm with the running time
that takes as
input a graph with maximum degree bounded by , parameters , ,
, and with probability at least , accepts the graph if it
is -clusterable and rejects the graph if it is -far from
-clusterable for , where depends only on . By the lower
bound of on the number of queries needed for testing graph
expansion, which corresponds to in our problem, our algorithm is
asymptotically optimal up to polylogarithmic factors.Comment: Full version of STOC 201
Towards a General Direct Product Testing Theorem
The Direct Product encoding of a string a in {0,1}^n on an underlying domain V subseteq ([n] choose k), is a function DP_V(a) which gets as input a set S in V and outputs a restricted to S. In the Direct Product Testing Problem, we are given a function F:V -> {0,1}^k, and our goal is to test whether F is close to a direct product encoding, i.e., whether there exists some a in {0,1}^n such that on most sets S, we have F(S)=DP_V(a)(S). A natural test is as follows: select a pair (S,S\u27)in V according to some underlying distribution over V x V, query F on this pair, and check for consistency on their intersection. Note that the above distribution may be viewed as a weighted graph over the vertex set V and is referred to as a test graph.
The testability of direct products was studied over various domains and test graphs: Dinur and Steurer (CCC \u2714) analyzed it when V equals the k-th slice of the Boolean hypercube and the test graph is a member of the Johnson graph family. Dinur and Kaufman (FOCS \u2717) analyzed it for the case where V is the set of faces of a Ramanujan complex, where in this case V=O_k(n). In this paper, we study the testability of direct products in a general setting, addressing the question: what properties of the domain and the test graph allow one to prove a direct product testing theorem?
Towards this goal we introduce the notion of coordinate expansion of a test graph. Roughly speaking a test graph is a coordinate expander if it has global and local expansion, and has certain nice intersection properties on sampling. We show that whenever the test graph has coordinate expansion then it admits a direct product testing theorem. Additionally, for every k and n we provide a direct product domain V subseteq (n choose k) of size n, called the Sliding Window domain for which we prove direct product testability
Characterisations and Examples of Graph Classes with Bounded Expansion
Classes with bounded expansion, which generalise classes that exclude a
topological minor, have recently been introduced by Ne\v{s}et\v{r}il and Ossona
de Mendez. These classes are defined by the fact that the maximum average
degree of a shallow minor of a graph in the class is bounded by a function of
the depth of the shallow minor. Several linear-time algorithms are known for
bounded expansion classes (such as subgraph isomorphism testing), and they
allow restricted homomorphism dualities, amongst other desirable properties. In
this paper we establish two new characterisations of bounded expansion classes,
one in terms of so-called topological parameters, the other in terms of
controlling dense parts. The latter characterisation is then used to show that
the notion of bounded expansion is compatible with Erd\"os-R\'enyi model of
random graphs with constant average degree. In particular, we prove that for
every fixed , there exists a class with bounded expansion, such that a
random graph of order and edge probability asymptotically almost
surely belongs to the class. We then present several new examples of classes
with bounded expansion that do not exclude some topological minor, and appear
naturally in the context of graph drawing or graph colouring. In particular, we
prove that the following classes have bounded expansion: graphs that can be
drawn in the plane with a bounded number of crossings per edge, graphs with
bounded stack number, graphs with bounded queue number, and graphs with bounded
non-repetitive chromatic number. We also prove that graphs with `linear'
crossing number are contained in a topologically-closed class, while graphs
with bounded crossing number are contained in a minor-closed class
Subset feedback vertex set is fixed parameter tractable
The classical Feedback Vertex Set problem asks, for a given undirected graph
G and an integer k, to find a set of at most k vertices that hits all the
cycles in the graph G. Feedback Vertex Set has attracted a large amount of
research in the parameterized setting, and subsequent kernelization and
fixed-parameter algorithms have been a rich source of ideas in the field.
In this paper we consider a more general and difficult version of the
problem, named Subset Feedback Vertex Set (SUBSET-FVS in short) where an
instance comes additionally with a set S ? V of vertices, and we ask for a set
of at most k vertices that hits all simple cycles passing through S. Because of
its applications in circuit testing and genetic linkage analysis SUBSET-FVS was
studied from the approximation algorithms perspective by Even et al.
[SICOMP'00, SIDMA'00].
The question whether the SUBSET-FVS problem is fixed-parameter tractable was
posed independently by Kawarabayashi and Saurabh in 2009. We answer this
question affirmatively. We begin by showing that this problem is
fixed-parameter tractable when parametrized by |S|. Next we present an
algorithm which reduces the given instance to 2^k n^O(1) instances with the
size of S bounded by O(k^3), using kernelization techniques such as the
2-Expansion Lemma, Menger's theorem and Gallai's theorem. These two facts allow
us to give a 2^O(k log k) n^O(1) time algorithm solving the Subset Feedback
Vertex Set problem, proving that it is indeed fixed-parameter tractable.Comment: full version of a paper presented at ICALP'1
Who Would be Interested in Services? An Entity Graph Learning System for User Targeting
With the growing popularity of various mobile devices, user targeting has
received a growing amount of attention, which aims at effectively and
efficiently locating target users that are interested in specific services.
Most pioneering works for user targeting tasks commonly perform
similarity-based expansion with a few active users as seeds, suffering from the
following major issues: the unavailability of seed users for newcoming services
and the unfriendliness of black-box procedures towards marketers. In this
paper, we design an Entity Graph Learning (EGL) system to provide explainable
user targeting ability meanwhile applicable to addressing the cold-start issue.
EGL System follows the hybrid online-offline architecture to satisfy the
requirements of scalability and timeliness. Specifically, in the offline stage,
the system focuses on the heavyweight entity graph construction and user entity
preference learning, in which we propose a Three-stage Relation Mining
Procedure (TRMP), breaking loose from the expensive seed users. At the online
stage, the system offers the ability of user targeting in real-time based on
the entity graph from the offline stage. Since the user targeting process is
based on graph reasoning, the whole process is transparent and
operation-friendly to marketers. Finally, extensive offline experiments and
online A/B testing demonstrate the superior performance of the proposed EGL
System.Comment: Accepted by ICDE 202
Testing first-order properties for subclasses of sparse graphs
We present a linear-time algorithm for deciding first-order (FO) properties
in classes of graphs with bounded expansion, a notion recently introduced by
Nesetril and Ossona de Mendez. This generalizes several results from the
literature, because many natural classes of graphs have bounded expansion:
graphs of bounded tree-width, all proper minor-closed classes of graphs, graphs
of bounded degree, graphs with no subgraph isomorphic to a subdivision of a
fixed graph, and graphs that can be drawn in a fixed surface in such a way that
each edge crosses at most a constant number of other edges. We deduce that
there is an almost linear-time algorithm for deciding FO properties in classes
of graphs with locally bounded expansion.
More generally, we design a dynamic data structure for graphs belonging to a
fixed class of graphs of bounded expansion. After a linear-time initialization
the data structure allows us to test an FO property in constant time, and the
data structure can be updated in constant time after addition/deletion of an
edge, provided the list of possible edges to be added is known in advance and
their simultaneous addition results in a graph in the class. All our results
also hold for relational structures and are based on the seminal result of
Nesetril and Ossona de Mendez on the existence of low tree-depth colorings
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