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CVPR
2007
IEEE
14 years 9 months ago
Element Rearrangement for Tensor-Based Subspace Learning
The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
Shuicheng Yan, Dong Xu, Stephen Lin, Thomas S. Hua...
AAAI
2011
12 years 7 months ago
Differential Eligibility Vectors for Advantage Updating and Gradient Methods
In this paper we propose differential eligibility vectors (DEV) for temporal-difference (TD) learning, a new class of eligibility vectors designed to bring out the contribution of...
Francisco S. Melo
TFS
2008
94views more  TFS 2008»
13 years 7 months ago
Hierarchical Fuzzy CMAC for Nonlinear Systems Modeling
Abstract--Since the fuzzy cerebellar model articulation controller (FCMAC) uses linguistic variables, it is highly intuitive and easily comprehended. Despite the FCMAC's good ...
Wen Yu, Floriberto Ortiz Rodriguez, Marco A. Moren...
ICMLA
2009
13 years 5 months ago
Transformation Learning Via Kernel Alignment
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
Andrew Howard, Tony Jebara
STOC
2005
ACM
129views Algorithms» more  STOC 2005»
14 years 8 months ago
Learning with attribute costs
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
Haim Kaplan, Eyal Kushilevitz, Yishay Mansour