48 search results - page 5 / 10 » Entropy and Margin Maximization for Structured Output Learni... |
104
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TKDE
2008
14 years 9 months ago
2008
One of the fundamental problems in Content-Based Image Retrieval (CBIR) has been the gap between low-level visual features and high-level semantic concepts. To narrow down this gap...
JMLR
2012
12 years 12 months ago
2012
We consider the task of devising large-margin based surrogate losses for the learning to rank problem. In this learning to rank setting, the traditional hinge loss for structured ...
KDD
2007
ACM
15 years 10 months ago
2007
ACM
The problem of multimodal data mining in a multimedia database can be addressed as a structured prediction problem where we learn the mapping from an input to the structured and i...
118
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TNN
2010
14 years 4 months ago
2010
Clustering using the Hilbert Schmidt independence criterion (CLUHSIC) is a recent clustering algorithm that maximizes the dependence between cluster labels and data observations ac...
77
Voted
JMLR
2010
14 years 4 months ago
2010
Various supervised inference methods can be analyzed as convex duals of the generalized maximum entropy (MaxEnt) framework. Generalized MaxEnt aims to find a distribution that max...