This paper introduces a semi-supervised distance metric learning algorithm which uses pair-wise equivalence (similarity and dissimilarity) constraints to improve the original dist...
This paper studies the problem of learning a full range of pairwise affinities gained by integrating local grouping cues for spectral segmentation. The overall quality of the spect...
Tae Hoon Kim (Seoul National University), Kyoung M...
This paper presents a new spectral partitioning formulation which directly incorporates vertex size information. The new formulation results in a generalized eigenvalue problem, a...
Abstract: We have developed a fitting algorithm able to extract spectral and dynamic properties of a three level oscillator from a two-dimensional infrared spectrum (2D-IR) detecte...
Riccardo Chelli, Victor V. Volkov, Roberto Righini
We propose a spectral partitioning approach for large-scale optimization problems, specifically structure from motion. In structure from motion, partitioning methods reduce the pr...