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» Robust Reductions from Ranking to Classification
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ICASSP
2010
IEEE
13 years 7 months ago
A nullspace analysis of the nuclear norm heuristic for rank minimization
The problem of minimizing the rank of a matrix subject to linear equality constraints arises in applications in machine learning, dimensionality reduction, and control theory, and...
Krishnamurthy Dvijotham, Maryam Fazel
BMCBI
2004
167views more  BMCBI 2004»
13 years 7 months ago
Feature selection for splice site prediction: A new method using EDA-based feature ranking
Background: The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Oth...
Yvan Saeys, Sven Degroeve, Dirk Aeyels, Pierre Rou...
AAAI
2008
13 years 9 months ago
Hypothesis Pruning and Ranking for Large Plan Recognition Problems
This paper addresses the problem of plan recognition for multi-agent teams. Complex multi-agent tasks typically require dynamic teams where the team membership changes over time. ...
Gita Sukthankar, Katia P. Sycara
ICCV
2011
IEEE
12 years 7 months ago
Latent Low-Rank Representation for Subspace Segmentation and Feature Extraction
Low-Rank Representation (LRR) [16, 17] is an effective method for exploring the multiple subspace structures of data. Usually, the observed data matrix itself is chosen as the dic...
Guangcan Liu, Shuicheng Yan
RSS
2007
135views Robotics» more  RSS 2007»
13 years 8 months ago
Learning omnidirectional path following using dimensionality reduction
Abstract— We consider the task of omnidirectional path following for a quadruped robot: moving a four-legged robot along any arbitrary path while turning in any arbitrary manner....
J. Zico Kolter, Andrew Y. Ng