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» Learning and Inference with Constraints
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AAAI
2011
14 years 6 months ago
Quantity Makes Quality: Learning with Partial Views
In many real world applications, the number of examples to learn from is plentiful, but we can only obtain limited information on each individual example. We study the possibiliti...
Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, O...
CVPR
2012
IEEE
13 years 9 months ago
Submodular dictionary learning for sparse coding
A greedy-based approach to learn a compact and discriminative dictionary for sparse representation is presented. We propose an objective function consisting of two components: ent...
Zhuolin Jiang, Guangxiao Zhang, Larry S. Davis
IJCAI
1997
15 years 8 months ago
Combining Probabilistic Population Codes
We study the problemof statisticallycorrect inference in networks whose basic representations are population codes. Population codes are ubiquitous in the brain, and involve the s...
Richard S. Zemel, Peter Dayan
BMCBI
2006
239views more  BMCBI 2006»
15 years 6 months ago
Applying dynamic Bayesian networks to perturbed gene expression data
Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...
Norbert Dojer, Anna Gambin, Andrzej Mizera, Bartek...
PAMI
2012
13 years 9 months ago
Recursive Segmentation and Recognition Templates for Image Parsing
— Language and image understanding are two major goals of artificial intelligence which can both be conceptually formulated in terms of parsing the input signal into a hierarchi...
Long Zhu, Yuanhao Chen, Yuan Lin, Chenxi Lin, Alan...