Knowledge graphs have received intensive research interests. When the labels of most nodes or datapoints are missing, anchor graph and hierarchical models can be employed. With an graph, we only need to optimize coarsest anchors, inferred from these anchors in a coarse-to-fine manner. The complexity optimization is therefore reduced cubic cost with respect number anchors. However, obtain high a...

In this paper, we relate the problem of finding a maximum clique to the intersection number of the input graph (i.e. the minimum number of cliques needed to edge cover the graph). In particular, we consider the maximum clique problem for graphs with small intersection number and random intersection graphs (a model in which each one of m labels is chosen independently with probability p by each ...

A divisor cordial labeling of a graph G with vertex set V is a bijection f from V to {1, 2,... | |} V such that an edge uv is assigned the label 1 if either ( ) | ( ) f u f v or ( ) | ( ) f v f u and the label 0 if ( ) ( ) f u f v , then number of edges labeled with 0 and the number of edges labeled with 1 differ by at most 1. A graph with a divisor cordial labeling is called a divisor cordial ...

Given a directed graph G = (V, A) (with n = |V | and m = |A|) with a length function : A → R + and a pair of vertices s, t, a distance oracle returns the distance dist(s, t) from s to t. A labeling algorithm [18] implements distance oracles in two stages. The preprocessing stage computes a label for each vertex of the input graph. Then, given s and t, the query stage computes dist(s, t) using o...

Graph-based semi-supervised learning has recently emerged as a promising approach to data-sparse learning problems in natural language processing. All graph-based algorithms rely on a graph that jointly represents labeled and unlabeled data points. The problem of how to best construct this graph remains largely unsolved. In this paper we introduce a data-driven method that optimizes the represe...

For a graph property P and a graph G, a subset S of the vertices of G is a P-set if the subgraph induced by S has the property P. A P-Roman dominating function on a graph G is a labeling f : V (G) → {0, 1, 2} such that every vertex with label 0 has a neighbor with label 2 and the set of all vertices with label 1 or 2 is a P-set. The P-Roman domination number γPR(G) of G is the minimum of Σv∈V (...

The abundant images and user-provided tags available on social media websites provide an intriguing opportunity to scale vision problems beyond the limits imposed by manual dataset collection and annotation. However, exploiting user-tagged data in practice is challenging since it contains many noisy (incorrect and missing) labels. In this work, we propose a novel robust graph-based approach for...

We describe a new approach to disambiguating semantic frames evoked by lexical predicates previously unseen in a lexicon or annotated data. Our approach makes use of large amounts of unlabeled data in a graph-based semi-supervised learning framework. We construct a large graph where vertices correspond to potential predicates and use label propagation to learn possible semantic frames for new o...