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» Structure learning of Bayesian networks using constraints
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ICML
2008
IEEE
16 years 21 days ago
Accurate max-margin training for structured output spaces
Tsochantaridis et al. (2005) proposed two formulations for maximum margin training of structured spaces: margin scaling and slack scaling. While margin scaling has been extensivel...
Sunita Sarawagi, Rahul Gupta
NPL
1998
87views more  NPL 1998»
14 years 11 months ago
Constrained Learning in Neural Networks: Application to Stable Factorization of 2-D Polynomials
Adaptive artificial neural network techniques are introduced and applied to the factorization of 2-D second order polynomials. The proposed neural network is trained using a const...
Stavros J. Perantonis, Nikolaos Ampazis, Stavros V...
WWW
2009
ACM
16 years 17 days ago
Enhancing diversity, coverage and balance for summarization through structure learning
Document summarization plays an increasingly important role with the exponential growth of documents on the Web. Many supervised and unsupervised approaches have been proposed to ...
Liangda Li, Ke Zhou, Gui-Rong Xue, Hongyuan Zha, Y...
CVPR
2009
IEEE
15 years 6 months ago
Learning multi-modal densities on Discriminative Temporal Interaction Manifold for group activity recognition
While video-based activity analysis and recognition has received much attention, existing body of work mostly deals with single object/person case. Coordinated multi-object activi...
Ruonan Li, Rama Chellappa, Shaohua Kevin Zhou
ICTAI
2009
IEEE
14 years 9 months ago
A Generalized Cyclic-Clustering Approach for Solving Structured CSPs
We propose a new method for solving structured CSPs which generalizes and improves the Cyclic-Clustering approach [4]. First, the cutset and the tree-decomposition of the constrai...
Cédric Pinto, Cyril Terrioux