Sciweavers

11 search results - page 1 / 3
» Scalable Tensor Factorizations for Incomplete Data
Sort
View
CORR
2010
Springer
255views Education» more  CORR 2010»
13 years 4 months ago
Scalable Tensor Factorizations for Incomplete Data
The problem of incomplete data--i.e., data with missing or unknown values--in multi-way arrays is ubiquitous in biomedical signal processing, network traffic analysis, bibliometri...
Evrim Acar, Tamara G. Kolda, Daniel M. Dunlavy, Mo...
ICDM
2008
IEEE
141views Data Mining» more  ICDM 2008»
13 years 11 months ago
Scalable Tensor Decompositions for Multi-aspect Data Mining
Modern applications such as Internet traffic, telecommunication records, and large-scale social networks generate massive amounts of data with multiple aspects and high dimensiona...
Tamara G. Kolda, Jimeng Sun
SDM
2010
SIAM
204views Data Mining» more  SDM 2010»
13 years 6 months ago
Scalable Tensor Factorizations with Missing Data
The problem of missing data is ubiquitous in domains such as biomedical signal processing, network traffic analysis, bibliometrics, social network analysis, chemometrics, computer...
Evrim Acar, Daniel M. Dunlavy, Tamara G. Kolda, Mo...
ICDM
2009
IEEE
202views Data Mining» more  ICDM 2009»
13 years 2 months ago
Link Prediction on Evolving Data Using Matrix and Tensor Factorizations
Abstract--The data in many disciplines such as social networks, web analysis, etc. is link-based, and the link structure can be exploited for many different data mining tasks. In t...
Evrim Acar, Daniel M. Dunlavy, Tamara G. Kolda
CIKM
2010
Springer
13 years 3 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 significant characteristics from polyadic data, such as data in s...
Yun Chi, Shenghuo Zhu