In this paper, we present a novel feature extraction framework, called learning by propagability. The whole learning process is driven by the philosophy that the data labels and o...
Bingbing Ni, Shuicheng Yan, Ashraf A. Kassim, Loon...
Classifications have been used for centuries with the goal of cataloguing and searching large sets of objects. In the early days it was mainly books; lately it has also become Web ...
In this paper, we propose a novel Markov model-based formulation for the image annotation problem. In this formulation, we treat image annotation as a graph ranking problem, by de...
Mallows and Riordan showed in 1968 that labeled trees with a small number of inversions are related to labeled graphs that are connected and sparse. Wright enumerated sparse connec...
Most previously proposed frequent graph mining algorithms are intended to find the complete set of all frequent, closed subgraphs. However, in many cases only a subset of the freq...