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TASLP
2008
120views more  TASLP 2008»
13 years 7 months ago
Rapid Speaker Adaptation Using Clustered Maximum-Likelihood Linear Basis With Sparse Training Data
Abstract-- Speaker space based adaptation methods for automatic speech recognition have been shown to provide significant performance improvements for tasks where only a few second...
Yun Tang, Richard Rose
JMLR
2012
11 years 9 months ago
Multi-label Subspace Ensemble
A challenging problem of multi-label learning is that both the label space and the model complexity will grow rapidly with the increase in the number of labels, and thus makes the...
Tianyi Zhou, Dacheng Tao
SDM
2009
SIAM
202views Data Mining» more  SDM 2009»
14 years 4 months ago
Proximity-Based Anomaly Detection Using Sparse Structure Learning.
We consider the task of performing anomaly detection in highly noisy multivariate data. In many applications involving real-valued time-series data, such as physical sensor data a...
Tsuyoshi Idé, Aurelie C. Lozano, Naoki Abe,...
ICASSP
2010
IEEE
13 years 7 months ago
Robust regression using sparse learning for high dimensional parameter estimation problems
Algorithms such as Least Median of Squares (LMedS) and Random Sample Consensus (RANSAC) have been very successful for low-dimensional robust regression problems. However, the comb...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
CORR
2010
Springer
84views Education» more  CORR 2010»
13 years 4 months ago
A Robust Beamformer Based on Weighted Sparse Constraint
Applying a sparse constraint on the beam pattern has been suggested to suppress the sidelobe level of a minimum variance distortionless response (MVDR) beamformer. In this letter, ...
Yipeng Liu, Qun Wan, Xiaoli Chu