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CORR
2011
Springer
168views Education» more  CORR 2011»
13 years 2 months ago
Submodular meets Spectral: Greedy Algorithms for Subset Selection, Sparse Approximation and Dictionary Selection
We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. This problem can ...
Abhimanyu Das, David Kempe
AAAI
2007
13 years 10 months ago
Compact Spectral Bases for Value Function Approximation Using Kronecker Factorization
A new spectral approach to value function approximation has recently been proposed to automatically construct basis functions from samples. Global basis functions called proto-val...
Jeffrey Johns, Sridhar Mahadevan, Chang Wang
ICML
2009
IEEE
14 years 8 months ago
On sampling-based approximate spectral decomposition
This paper addresses the problem of approximate singular value decomposition of large dense matrices that arises naturally in many machine learning applications. We discuss two re...
Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar
EDUTAINMENT
2010
Springer
13 years 6 months ago
Spectrally-Based Single Image Relighting
Abstract. This paper presents a new spectrally-based single image relighting approach. We first compute the spectral radiance of each stimulus on the monitor when displaying the i...
Xiaoxiong Xing, Weiming Dong, Xiaopeng Zhang, Jean...
PAMI
2010
192views more  PAMI 2010»
13 years 6 months ago
Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA
—A new formulation for multiway spectral clustering is proposed. This method corresponds to a weighted kernel principal component analysis (PCA) approach based on primal-dual lea...
Carlos Alzate, Johan A. K. Suykens