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» Rank Estimation in Missing Data Matrix Problems
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CORR
2010
Springer
105views Education» more  CORR 2010»
13 years 6 months ago
Online Identification and Tracking of Subspaces from Highly Incomplete Information
This work presents GROUSE (Grassmanian Rank-One Update Subspace Estimation), an efficient online algorithm for tracking subspaces from highly incomplete observations. GROUSE requi...
Laura Balzano, Robert Nowak, Benjamin Recht
HIS
2004
13 years 7 months ago
K-Ranked Covariance Based Missing Values Estimation for Microarray Data Classification
Microarray data often contains multiple missing genetic expression values that degrade the performance of statistical and machine learning algorithms. This paper presents a K rank...
Muhammad Shoaib B. Sehgal, Iqbal Gondal, Laurence ...
ICB
2009
Springer
132views Biometrics» more  ICB 2009»
13 years 4 months ago
Fusion in Multibiometric Identification Systems: What about the Missing Data?
Many large-scale biometric systems operate in the identification mode and include multimodal information. While biometric fusion is a well-studied problem, most of the fusion schem...
Karthik Nandakumar, Anil K. Jain, Arun Ross
KDD
2012
ACM
201views Data Mining» more  KDD 2012»
11 years 8 months ago
Low rank modeling of signed networks
Trust networks, where people leave trust and distrust feedback, are becoming increasingly common. These networks may be regarded as signed graphs, where a positive edge weight cap...
Cho-Jui Hsieh, Kai-Yang Chiang, Inderjit S. Dhillo...
AINA
2008
IEEE
14 years 21 days ago
Missing Value Estimation for Time Series Microarray Data Using Linear Dynamical Systems Modeling
The analysis of gene expression time series obtained from microarray experiments can be effectively exploited to understand a wide range of biological phenomena from the homeostat...
Connie Phong, Raul Singh