48 search results - page 6 / 10 » Entropy and Margin Maximization for Structured Output Learni... |
ICPR
2008
IEEE
15 years 4 months ago
2008
IEEE
In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neig...
JMLR
2010
14 years 4 months ago
2010
Structured prediction tasks pose a fundamental trade-off between the need for model complexity to increase predictive power and the limited computational resources for inference i...
CORR
2010
Springer
14 years 7 months ago
2010
Springer
Structured output prediction is an important machine learning problem both in theory and practice, and the max-margin Markov network (M3 N) is an effective approach. All state-of-...
NIPS
2003
14 years 11 months ago
2003
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
NIPS
2003
14 years 11 months ago
2003
In order to understand AdaBoost’s dynamics, especially its ability to maximize margins, we derive an associated simplified nonlinear iterated map and analyze its behavior in lo...