We prove that various geometric covering problems, related to the Travelling Salesman Problem cannot be efficiently approximated to within any constant factor unless P = NP. This ...
In recent years the Markov Random Field (MRF) has
become the de facto probabilistic model for low-level vision
applications. However, in a maximum a posteriori
(MAP) framework, ...
Oliver J. Woodford, Carsten Rother, Vladimir Kolmo...
In kernel methods, an interesting recent development seeks to learn a good kernel from empirical data automatically. In this paper, by regarding the transductive learning of the k...
Recognition of objects in highly structured surroundings is a challenging task, because the appearance of target objects changes due to fluctuations in their surroundings. This ma...
Vincent Frans van Ravesteijn, Frans M. Vos, Lucas ...
Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, the problems of interest become increasingly challenging and complex. Makin...
Ming-Wei Chang, Lev-Arie Ratinov, Nicholas Rizzolo...