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NIPS
2001
13 years 7 months ago
Speech Recognition with Missing Data using Recurrent Neural Nets
In the `missing data' approach to improving the robustness of automatic speech recognition to added noise, an initial process identifies spectraltemporal regions which are do...
S. Parveen, P. Green
ICPR
2004
IEEE
14 years 7 months ago
Human Action Segmentation via Controlled Use of Missing Data in HMMs
Segmentation of individual actions from a stream of human motion is an open problem in computer vision. This paper approaches the problem of segmenting higher-level activities int...
Patrick Peursum, Hung Hai Bui, Svetha Venkatesh, G...
AINA
2008
IEEE
14 years 19 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
IJCNN
2007
IEEE
14 years 13 days ago
Random Feature Subset Selection for Analysis of Data with Missing Features
Abstract - We discuss an ensemble-of-classifiers based algorithm for the missing feature problem. The proposed approach is inspired in part by the random subspace method, and in pa...
Joseph DePasquale, Robi Polikar
DAWAK
2009
Springer
14 years 28 days ago
Dynamic Clustering-Based Estimation of Missing Values in Mixed Type Data
The appropriate choice of a method for imputation of missing data becomes especially important when the fraction of missing values is large and the data are of mixed type. The prop...
Vadim V. Ayuyev, Joseph Jupin, Philip W. Harris, Z...