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» A Parameter-Free Associative Classification Method
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ICML
2009
IEEE
14 years 9 months ago
Learning kernels from indefinite similarities
Similarity measures in many real applications generate indefinite similarity matrices. In this paper, we consider the problem of classification based on such indefinite similariti...
Yihua Chen, Maya R. Gupta, Benjamin Recht
ICASSP
2009
IEEE
14 years 15 days ago
High-level feature extraction using SVM with walk-based graph kernel
We investigate a method using support vector machines (SVMs) with walk-based graph kernels for high-level feature extraction from images. In this method, each image is first segme...
Jean-Philippe Vert, Tomoko Matsui, Shin'ichi Satoh...
TRECVID
2008
13 years 10 months ago
ISM TRECVID2008 High-level Feature Extraction
We studied a method using support vector machines (SVMs) with walk-based graph kernels for the high-level feature extraction (HLF) task. In this method, each image is first segmen...
Tomoko Matsui, Jean-Philippe Vert, Shin'ichi Satoh...
KBS
2006
79views more  KBS 2006»
13 years 8 months ago
Using multiple and negative target rules to make classifiers more understandable
One major goal for data mining is to understand data. Rule based methods are better than other methods in making mining results comprehensible. However, the current rule based cla...
Jiuyong Li, Jason Jones
ICCV
2007
IEEE
14 years 15 days ago
ClassMap: Efficient Multiclass Recognition via Embeddings
In many computer vision applications, such as face recognition and hand pose estimation, we need systems that can recognize a very large number of classes. Large margin classifica...
Vassilis Athitsos, Alexandra Stefan, Quan Yuan, St...