In order to evaluate the performance of information retrieval and extraction algorithms, we need test collections. A test collection consists of a set of documents, a clearly form...
The multi-label problem is of fundamental importance to computer vision, yet finding global minima of the associated energies is very hard and usually impossible in practice. Rec...
Evgeny Strekalovskiy, Bastian Goldluecke, Daniel C...
Crowdsourcing platforms offer unprecedented opportunities for creating evaluation benchmarks, but suffer from varied output quality from crowd workers who possess different levels...
We present a simple, agnostic active learning algorithm that works for any hypothesis class of bounded VC dimension, and any data distribution. Our algorithm extends a scheme of C...
Markov random field (MRF) theory has widely been applied to segmentation in noisy images. This paper proposes a new MRF method. First, it couples the original labeling MRF with a ...