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» Objective Functions for Feature Discrimination
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ML
2002
ACM
123views Machine Learning» more  ML 2002»
13 years 10 months ago
Feature Generation Using General Constructor Functions
Most classification algorithms receive as input a set of attributes of the classified objects. In many cases, however, the supplied set of attributes is not sufficient for creatin...
Shaul Markovitch, Dan Rosenstein
CVPR
2009
IEEE
14 years 5 months ago
Saliency-based discriminant tracking
We propose a biologically inspired framework for visual tracking based on discriminant center surround saliency. At each frame, discrimination of the target from the background is...
Vijay Mahadevan, Nuno Vasconcelos
ICML
2004
IEEE
14 years 4 months ago
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
Hisashi Kashima, Yuta Tsuboi
CVPR
2005
IEEE
15 years 1 months ago
Object Detection Using 2D Spatial Ordering Constraints
Object detection is challenging partly due to the limited discriminative power of local feature descriptors. We amend this limitation by incorporating spatial constraints among ne...
Yan Li, Yanghai Tsin, Yakup Genc, Takeo Kanade
EMNLP
2007
14 years 13 days ago
Semi-Supervised Structured Output Learning Based on a Hybrid Generative and Discriminative Approach
This paper proposes a framework for semi-supervised structured output learning (SOL), specifically for sequence labeling, based on a hybrid generative and discriminative approach...
Jun Suzuki, Akinori Fujino, Hideki Isozaki