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» Learning large margin classifiers locally and globally
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PAMI
2011
12 years 10 months ago
Hidden Part Models for Human Action Recognition: Probabilistic versus Max Margin
—We present a discriminative part-based approach for human action recognition from video sequences using motion features. Our model is based on the recently proposed hidden condi...
Yang Wang 0003, Greg Mori
ICPR
2008
IEEE
14 years 8 months ago
Prototype learning with margin-based conditional log-likelihood loss
The classification performance of nearest prototype classifiers largely relies on the prototype learning algorithms, such as the learning vector quantization (LVQ) and the minimum...
Cheng-Lin Liu, Xiaobo Jin, Xinwen Hou
ACCV
2010
Springer
13 years 2 months ago
Pedestrian Recognition with a Learned Metric
This paper presents a new method for viewpoint invariant pedestrian recognition problem. We use a metric learning framework to obtain a robust metric for large margin nearest neigh...
Mert Dikmen, Emre Akbas, Thomas S. Huang, Narendra...
ICDM
2008
IEEE
156views Data Mining» more  ICDM 2008»
14 years 2 months ago
Exploiting Local and Global Invariants for the Management of Large Scale Information Systems
This paper presents a data oriented approach to modeling the complex computing systems, in which an ensemble of correlation models are discovered to represent the system status. I...
Haifeng Chen, Haibin Cheng, Guofei Jiang, Kenji Yo...
CVPR
2009
IEEE
15 years 2 months ago
Contextual Classification with Functional Max-Margin Markov Networks
We address the problem of label assignment in computer vision: given a novel 3-D or 2-D scene, we wish to assign a unique label to every site (voxel, pixel, superpixel, etc.). To...
Daniel Munoz, James A. Bagnell, Martial Hebert, Ni...