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ICML
2006
IEEE
16 years 7 months ago
Bayesian regression with input noise for high dimensional data
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
CSB
2005
IEEE
126views Bioinformatics» more  CSB 2005»
15 years 12 months ago
Discover True Association Rates in Multi-protein Complex Proteomics Data Sets
Experimental processes to collect and process proteomics data are increasingly complex, while the computational methods to assess the quality and significance of these data remain...
Changyu Shen, Lang Li, Jake Yue Chen
CVPR
2004
IEEE
16 years 8 months ago
Incremental Density Approximation and Kernel-Based Bayesian Filtering for Object Tracking
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...
NIPS
1996
15 years 7 months ago
Interpreting Images by Propagating Bayesian Beliefs
A central theme of computational vision research has been the realization that reliable estimation of local scene properties requires propagating measurements across the image. Ma...
Yair Weiss
CVPR
2004
IEEE
16 years 8 months ago
Bayesian Assembly of 3D Axially Symmetric Shapes from Fragments
We present a complete system for the purpose of automatically assembling 3D pots given 3D measurements of their fragments commonly called sherds. A Bayesian approach is formulated...
Andrew R. Willis, David B. Cooper