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...
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...
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...
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...
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...