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NLE
2010
112views more  NLE 2010»
9 years 10 months ago
A non-negative tensor factorization model for selectional preference induction
Distributional similarity methods have proven to be a valuable tool for the induction of semantic similarity. Up till now, most algorithms use two-way cooccurrence data to compute...
Tim Van de Cruys
CIKM
2010
Springer
9 years 10 months ago
FacetCube: a framework of incorporating prior knowledge into non-negative tensor factorization
Non-negative tensor factorization (NTF) is a relatively new technique that has been successfully used to extract signi´Čücant characteristics from polyadic data, such as data in s...
Yun Chi, Shenghuo Zhu
BIBE
2007
IEEE
159views Bioinformatics» more  BIBE 2007»
10 years 3 months ago
Non-negative Tensor Factorization Based on Alternating Large-scale Non-negativity-constrained Least Squares
Non-negative matrix factorization (NMF) and non-negative tensor factorization (NTF) have attracted much attention and have been successfully applied to numerous data analysis probl...
Hyunsoo Kim, Haesun Park, Lars Eldén
ICANNGA
2007
Springer
191views Algorithms» more  ICANNGA 2007»
10 years 5 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...
ECCV
2006
Springer
11 years 1 months ago
Controlling Sparseness in Non-negative Tensor Factorization
Non-negative tensor factorization (NTF) has recently been proposed as sparse and efficient image representation (Welling and Weber, Patt. Rec. Let., 2001). Until now, sparsity of t...
Matthias Heiler, Christoph Schnörr
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