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PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
16 years 1 months ago
The Feature Importance Ranking Measure
Most accurate predictions are typically obtained by learning machines with complex feature spaces (as e.g. induced by kernels). Unfortunately, such decision rules are hardly access...
Alexander Zien, Nicole Krämer, Sören Son...
TRECVID
2008
15 years 7 months ago
Peking University at TRECVID 2008: High Level Feature Extraction
We participated in one task of TRECVID 2008, that is, the high-level feature extraction (HLFE). This paper presents our approaches and results on the HLFE task. We mainly focus on...
Yuxin Peng, Zhiguo Yang, Jian Yi, Lei Cao, Hao Li,...
EMNLP
2009
15 years 4 months ago
A Rich Feature Vector for Protein-Protein Interaction Extraction from Multiple Corpora
Because of the importance of proteinprotein interaction (PPI) extraction from text, many corpora have been proposed with slightly differing definitions of proteins and PPI. Since ...
Makoto Miwa, Rune Sætre, Yusuke Miyao, Jun-i...
ICALT
2005
IEEE
16 years 1 days ago
An Ontology-Based Approach to Supporting Didactics in E-Learning Systems
Recent developments in E-Learning systems aim at providing a better support for didactics-aware learning scenarios. Typically, in order to provide that support the number and comp...
Denis Helic
ICCV
2005
IEEE
16 years 8 months ago
The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features
Discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. Kernel-based classification m...
Kristen Grauman, Trevor Darrell