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NN
2010
Springer
189views Neural Networks» more  NN 2010»
13 years 2 months ago
Sparse kernel learning with LASSO and Bayesian inference algorithm
Kernelized LASSO (Least Absolute Selection and Shrinkage Operator) has been investigated in two separate recent papers (Gao et al., 2008) and (Wang et al., 2007). This paper is co...
Junbin Gao, Paul W. Kwan, Daming Shi
SIBGRAPI
2005
IEEE
14 years 1 months ago
Particle Filter-Based Predictive Tracking for Robust Fish Counting
In this paper we study the use of computer vision techniques for for underwater visual tracking and counting of fishes in vivo. The methodology is based on the application of a B...
Erikson F. Morais, Mario Fernando Montenegro Campo...
ICML
2007
IEEE
14 years 8 months ago
Robust multi-task learning with t-processes
Most current multi-task learning frameworks ignore the robustness issue, which means that the presence of "outlier" tasks may greatly reduce overall system performance. ...
Shipeng Yu, Volker Tresp, Kai Yu
ICASSP
2009
IEEE
14 years 2 months ago
Modelling the prepausal lengthening effect for speech recognition: a dynamic Bayesian network approach
Speech has a property that the speech unit preceding a speech pause tends to lengthen. This work presents the use of a dynamic Bayesian network to model the prepausal lengthening ...
Ning Ma, Chris Bartels, Jeff A. Bilmes, Phil Green
ACCV
2009
Springer
14 years 2 months ago
Evolving Mean Shift with Adaptive Bandwidth: A Fast and Noise Robust Approach
Abstract. This paper presents a novel nonparametric clustering algorithm called evolving mean shift (EMS) algorithm. The algorithm iteratively shrinks a dataset and generates well ...
Qi Zhao, Zhi Yang, Hai Tao, Wentai Liu