arXiv subjects

Jun Yue

Publications and source records attributed to Jun Yue.

25 records · Page 2Linked to original sources

arXiv2016

Parallel K-Medoids++ Spatial Clustering Algorithm Based on MapReduce

Clustering analysis has received considerable attention in spatial data mining for several years. With the rapid development of the geospatial information technologies, the size of spatial information data is growing exponentially which makes clustering massive spatial data a challenging task. In order to improve the efficiency of spatial clustering for large scale data, many researchers proposed several efficient clustering algorithms in parallel. In this paper, a new K-Medoids++ spatial clustering algorithm based on MapReduce for clustering massive spatial data is proposed. The initialization algorithm to decrease the number of iterations is combined with the MapReduce framework. Comparative Experiments conducted over different dataset and different number of nodes indicate that the proposed K-Medoids spatial clustering algorithm provides better efficiency than traditional K-Medoids and scales well while processing massive spatial data on commodity hardware.

cs.DC↗

arXiv2016

Supervised multiview learning based on simultaneous learning of multiview intact and single view classifier

Multiview learning problem refers to the problem of learning a classifier from multiple view data. In this data set, each data points is presented by multiple different views. In this paper, we propose a novel method for this problem. This method is based on two assumptions. The first assumption is that each data point has an intact feature vector, and each view is obtained by a linear transformation from the intact vector. The second assumption is that the intact vectors are discriminative, and in the intact space, we have a linear classifier to separate the positive class from the negative class. We define an intact vector for each data point, and a view-conditional transformation matrix for each view, and propose to reconstruct the multiple view feature vectors by the product of the corresponding intact vectors and transformation matrices. Moreover, we also propose a linear classifier in the intact space, and learn it jointly with the intact vectors. The learning problem is modeled by a minimization problem, and the objective function is composed of a Cauchy error estimator-based view-conditional reconstruction term over all data points and views, and a classification error term measured by hinge loss over all the intact vectors of all the data points. Some regularization terms are also imposed to different variables in the objective function. The minimization problem is solve by an iterative algorithm using alternate optimization strategy and gradient descent algorithm. The proposed algorithm shows it advantage in the compression to other multiview learning algorithms on benchmark data sets.

cs.CV↗

arXiv2015

Proper connection number and connected dominating sets

The proper connection number $pc(G)$ of a connected graph $G$ is defined as the minimum number of colors needed to color its edges, so that every pair of distinct vertices of $G$ is connected by at least one path in $G$ such that no two adjacent edges of the path are colored the same, and such a path is called a proper path. In this paper, we show that for every connected graph with diameter 2 and minimum degree at least 2, its proper connection number is 2. Then, we give an upper bound $\frac{3n}{δ+ 1}-1$ for every connected graph of order $n$ and minimum degree $δ$. We also show that for every connected graph $G$ with minimum degree at least $2$, the proper connection number $pc(G)$ is upper bounded by $pc(G[D])+2$, where $D$ is a connected two-way (two-step) dominating set of $G$. Bounds of the form $pc(G)\leq 4$ or $pc(G)=2$, for many special graph classes follow as easy corollaries from this result, which include connected interval graphs, asteroidal triple-free graphs, circular arc graphs, threshold graphs and chain graphs, all with minimum degree at least $2$. Furthermore, we get the sharp upper bound 3 for the proper connection numbers of interval graphs and circular arc graphs through analyzing their structures.

math.CO↗

arXiv2014

The generalized 3-edge-connectivity of lexicographic product graphs

The generalized $k$-edge-connectivity $λ_k(G)$ of a graph $G$ is a generalization of the concept of edge-connectivity. The lexicographic product of two graphs $G$ and $H$, denoted by $G\circ H$, is an important graph product. In this paper, we mainly study the generalized 3-edge-connectivity of $G \circ H$, and get upper and lower bounds of $λ_3(G \circ H)$. Moreover, all bounds are sharp.

math.CO↗

arXiv2013

A Turán-type problem on distance two

A new turán-type problem on distances on graphs was introduced by Tyomkyn and Uzzell. In this paper, we focus on the case that the distance is two. We primely show that for any value of $n$, a graph on $n$ vertices without three vertices pairwise at distance $2$, if it has a vertex $v \in V(G)$, whose neighbours are covered by at most two cliques, then it has at most $(n^2 - 1)/4 + 1$ pairs of vertices at distance $2$. This partially answers a guess of Tyomkyn and Uzzell [Tyomkyn, M., Uzzell, A.J.: A new Turán-Type promble on distaces of graphs. Graphs Combin. {\bf 29}(6), 1927--1942 (2012)].

math.CO↗

arXiv2013

Lower bounds for the spanning tree numbers of two graph products

For any graph $G$ of order $n$, the spanning tree packing number \emph{$STP(G)$}, is the maximum number of edge-disjoint spanning trees contained in $G$. In this paper, we obtain some sharp lower bounds for the spanning tree numbers of Cartesian product graphs and Lexicographic product graphs.

math.CO↗

arXiv2011

Note on the oriented diameter of graphs with diameter 3

In 1978, Chvátal and Thomassen showed that every bridgeless graph with diameter 2 has an orientation with diameter at most 6. They also gave general bounds on the smallest value $f(d)$ such that every bridgeless graph $G$ with diameter $d$ has an orientation with diameter at most $f(d)$. For $d=3$, they proved that $8\leq f(d)\leq 24$. Until recently, Kwok, Liu and West improved the above bounds by proving $9\leq f(3)\leq 11$ in [P.K. Kwok, Q. Liu and D.B. West, Oriented diameter of graphs with diameter 3, J. Combin. Theory Ser.B 100(2010), 265-274]. In this paper, we determine the oriented diameter among the bridgeless graphs with diameter 3 that have minimum number of edges.

math.CO↗