48 search results - page 6 / 10 » Entropy and Margin Maximization for Structured Output Learni... |
164
Voted
ICPR
2008
IEEE
16 years 7 days 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...
186
Voted
JMLR
2010
15 years 18 days 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...
147
Voted
CORR
2010
Springer
15 years 4 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-...
192
Voted
NIPS
2003
15 years 7 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 ...
193
Voted
NIPS
2003
15 years 7 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...