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» Learning from Highly Structured Data by Decomposition
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ICTAI
2010
IEEE
14 years 7 months ago
Obtaining Bipartitions from Score Vectors for Multi-Label Classification
Multi-label classification is a popular learning task. However, some of the algorithms that learn from multi-label data, can only output a score for each label, so they cannot be r...
Marios Ioannou, George Sakkas, Grigorios Tsoumakas...
WWW
2009
ACM
15 years 10 months 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...
TIT
2010
97views Education» more  TIT 2010»
14 years 4 months ago
Why does the Kronecker model result in misleading capacity estimates?
Many recent works that study the performance of multi-input multi-output (MIMO) systems in practice assume a Kronecker model where the variances of the channel entries, upon decom...
Vasanthan Raghavan, Jayesh H. Kotecha, Akbar M. Sa...
ECCV
2004
Springer
15 years 12 months ago
Shape Reconstruction from 3D and 2D Data Using PDE-Based Deformable Surfaces
In this paper, we propose a new PDE-based methodology for deformable surfaces that is capable of automatically evolving its shape to capture the geometric boundary of the data and ...
Ye Duan, Liu Yang, Hong Qin, Dimitris Samaras
CIKM
2008
Springer
14 years 12 months ago
Identifying table boundaries in digital documents via sparse line detection
Most prior work on information extraction has focused on extracting information from text in digital documents. However, often, the most important information being reported in an...
Ying Liu, Prasenjit Mitra, C. Lee Giles