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NIPS
2007
15 years 5 months ago
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...
Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashi...
135
Voted
BMCBI
2006
100views more  BMCBI 2006»
15 years 3 months ago
Using the nucleotide substitution rate matrix to detect horizontal gene transfer
Background: Horizontal gene transfer (HGT) has allowed bacteria to evolve many new capabilities. Because transferred genes perform many medically important functions, such as conf...
Micah Hamady, M. D. Betterton, Rob Knight
132
Voted
SCA
2007
15 years 6 months ago
Time-critical distributed contact for 6-DoF haptic rendering of adaptively sampled reduced deformable models
Real-time evaluation of distributed contact forces for rigid or deformable 3D objects is important for providing multi-sensory feedback in emerging real-time applications, such as...
Jernej Barbic, Doug L. James
147
Voted
ISBI
2004
IEEE
16 years 4 months ago
A Fast Fully 4D Incremental Gradient Reconstruction Algorithm for List Mode PET Data
We present a fully four-dimensional, globally convergent, incremental gradient algorithm to estimate the continuous-time tracer density from list mode positron emission tomography...
Quanzheng Li, Evren Asma, Richard M. Leahy
173
Voted
CVPR
2010
IEEE
1790views Computer Vision» more  CVPR 2010»
15 years 12 months ago
Data Driven Mean-Shift Belief Propagation For non-Gaussian MRFs
We introduce a novel data-driven mean-shift belief propagation (DDMSBP) method for non-Gaussian MRFs, which often arise in computer vision applications. With the aid of scale sp...
Minwoo Park, S. Kashyap, R. Collins, and Y. Liu