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DOCENG
2009
ACM
14 years 4 months ago
Test collection management and labeling system
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...
Eunyee Koh, Andruid Kerne, Sarah Berry
ICCV
2011
IEEE
12 years 10 months ago
Tight Convex Relaxations for Vector-Valued Labeling Problems
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...
CIKM
2011
Springer
12 years 10 months ago
Worker types and personality traits in crowdsourcing relevance labels
Crowdsourcing platforms offer unprecedented opportunities for creating evaluation benchmarks, but suffer from varied output quality from crowd workers who possess different levels...
Gabriella Kazai, Jaap Kamps, Natasa Milic-Frayling
NIPS
2007
13 years 11 months ago
A general agnostic active learning algorithm
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...
Sanjoy Dasgupta, Daniel Hsu, Claire Monteleoni
ICIP
2005
IEEE
14 years 11 months ago
A segmentation method using compound Markov random fields based on a general boundary model
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 ...
Jue Wu, Albert C. S. Chung