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» Learning a Classification Model for Segmentation
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PCM
2010
Springer
183views Multimedia» more  PCM 2010»
15 years 3 months ago
Fast H.264 Encoding Based on Statistical Learning
Abstract. In this paper, we propose an efficient video coding system that applies statistical learning methods to reduce the computational cost in H.264 encoder. The proposed metho...
Chen-Kuo Chiang, Shang-Hong Lai
144
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CEC
2010
IEEE
15 years 2 months ago
Active Learning Genetic programming for record deduplication
The great majority of genetic programming (GP) algorithms that deal with the classification problem follow a supervised approach, i.e., they consider that all fitness cases availab...
Junio de Freitas, Gisele L. Pappa, Altigran Soares...
NECO
2007
127views more  NECO 2007»
15 years 4 months ago
Visual Recognition and Inference Using Dynamic Overcomplete Sparse Learning
We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and e...
Joseph F. Murray, Kenneth Kreutz-Delgado
CVPR
2007
IEEE
16 years 6 months ago
Concurrent Multiple Instance Learning for Image Categorization
We propose a new multiple instance learning (MIL) algorithm to learn image categories. Unlike existing MIL algorithms, in which the individual instances in a bag are assumed to be...
Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Tao Mei, Jin...
ICML
2007
IEEE
16 years 5 months ago
The matrix stick-breaking process for flexible multi-task learning
In multi-task learning our goal is to design regression or classification models for each of the tasks and appropriately share information between tasks. A Dirichlet process (DP) ...
Ya Xue, David B. Dunson, Lawrence Carin