y trees are well-known abstract structures. This paper proposes a new shape-based image retrieval method based on concavity trees. The proposed method has two main components. The...
We develop a machine-learned similarity metric for Windows failure reports using telemetry data gathered from clients describing the failures. The key feature is a tuned callstack...
Kevin Bartz, Jack W. Stokes, John C. Platt, Ryan K...
This paper develops a supervised dimensionality reduction method, Lorentzian Discriminant Projection (LDP), for discriminant analysis and classification. Our method represents the...
Simbed, standing for similarity-based embedding, is a new method of embedding high-dimensional data. It relies on the preservation of pairwise similarities rather than distances. I...
In this paper, we propose a novel 2D/3D approach for 3D model matching and retrieving. Each model is represented by a set of depth lines which will be afterward transformed into s...