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SIAMJO
2011
14 years 4 months ago
Recovering Low-Rank and Sparse Components of Matrices from Incomplete and Noisy Observations
Many applications arising in a variety of fields can be well illustrated by the task of recovering the low-rank and sparse components of a given matrix. Recently, it is discovered...
Min Tao, Xiaoming Yuan
ICANN
2007
Springer
15 years 3 months ago
Sparse and Transformation-Invariant Hierarchical NMF
The hierarchical non-negative matrix factorization (HNMF) is a multilayer generative network for decomposing strictly positive data into strictly positive activations and base vect...
Sven Rebhan, Julian Eggert, Horst-Michael Gro&szli...
ICANNGA
2007
Springer
191views Algorithms» more  ICANNGA 2007»
15 years 3 months ago
Novel Multi-layer Non-negative Tensor Factorization with Sparsity Constraints
In this paper we present a new method of 3D non-negative tensor factorization (NTF) that is robust in the presence of noise and has many potential applications, including multi-way...
Andrzej Cichocki, Rafal Zdunek, Seungjin Choi, Rob...
DAC
2004
ACM
15 years 10 months ago
Sparse transformations and preconditioners for hierarchical 3-D capacitance extraction with multiple dielectrics
Capacitance extraction is an important problem that has been extensively studied. This paper presents a significant improvement for the fast multipole accelerated boundary element...
Shu Yan, Vivek Sarin, Weiping Shi
ALT
2008
Springer
15 years 6 months ago
Generalization Bounds for K-Dimensional Coding Schemes in Hilbert Spaces
We give a bound on the expected reconstruction error for a general coding method where data in a Hilbert space are represented by finite dimensional coding vectors. The result can...
Andreas Maurer, Massimiliano Pontil