52 search results - page 2 / 11 » Structured Output Learning with High Order Loss Functions |
ICML
2008
IEEE
14 years 5 months ago
2008
IEEE
Tsochantaridis et al. (2005) proposed two formulations for maximum margin training of structured spaces: margin scaling and slack scaling. While margin scaling has been extensivel...
ECML
2006
Springer
13 years 8 months ago
2006
Springer
In many complex machine learning applications there is a need to learn multiple interdependent output variables, where knowledge of these interdependencies can be exploited to impr...
NIPS
2008
13 years 6 months ago
2008
Ranking is at the heart of many information retrieval applications. Unlike standard regression or classification in which we predict outputs independently, in ranking we are inter...
EMNLP
2011
12 years 4 months ago
2011
We propose a general method to watermark and probabilistically identify the structured outputs of machine learning algorithms. Our method is robust to local editing operations and...
CVPR
2009
IEEE
14 years 9 months ago
2009
IEEE
Structured outputs such as multidimensional vectors or graphs are frequently encountered in real world pattern recognition applications such as computer vision, natural language pr...