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WWW
2011
ACM
14 years 6 months ago
Learning to rank with multiple objective functions
We investigate the problem of learning to rank for document retrieval from the perspective of learning with multiple objective functions. We present solutions to two open problems...
Krysta Marie Svore, Maksims Volkovs, Christopher J...
AMDO
2006
Springer
15 years 3 months ago
Efficient Incorporation of Motionless Foreground Objects for Adaptive Background Segmentation
In this paper, we want to exploit the knowledge obtained from those detected objects which are incorporated into the background model since they cease their movement. These motionl...
Ivan Huerta Casado, Daniel Rowe, Jordi Gonzà...
HIS
2007
15 years 1 months ago
Pareto-based Multi-Objective Machine Learning
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...
Yaochu Jin
LREC
2008
139views Education» more  LREC 2008»
15 years 1 months ago
Automatic Learning and Evaluation of User-Centered Objective Functions for Dialogue System Optimisation
The ultimate goal when building dialogue systems is to satisfy the needs of real users, but quality assurance for dialogue strategies is a non-trivial problem. The applied evaluat...
Verena Rieser, Oliver Lemon
ECCV
2010
Springer
15 years 5 months ago
On Parameter Learning in CRF-based Approaches to Object Class Image Segmentation
Recent progress in per-pixel object class labeling of natural images can be attributed to the use of multiple types of image features and sound statistical learning approaches. Wit...