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NN
2010
Springer
183views Neural Networks» more  NN 2010»
14 years 8 months ago
Dimensionality reduction for density ratio estimation in high-dimensional spaces
The ratio of two probability density functions is becoming a quantity of interest these days in the machine learning and data mining communities since it can be used for various d...
Masashi Sugiyama, Motoaki Kawanabe, Pui Ling Chui
73
Voted
ICML
2005
IEEE
15 years 10 months ago
Predicting probability distributions for surf height using an ensemble of mixture density networks
There is a range of potential applications of Machine Learning where it would be more useful to predict the probability distribution for a variable rather than simply the most lik...
Michael Carney, Padraig Cunningham, Jim Dowling, C...
ICCAD
2002
IEEE
73views Hardware» more  ICCAD 2002»
15 years 6 months ago
Shaping interconnect for uniform current density
As the VLSI technology scaling down, the electromigration problem becomes one of the major concerns in high-performance IC design for both power network and signal interconnects. ...
Muzhou Shao, D. F. Wong, Youxin Gao, Li-Pen Yuan, ...
IJCV
2006
266views more  IJCV 2006»
14 years 9 months ago
Kernel Density Estimation and Intrinsic Alignment for Shape Priors in Level Set Segmentation
In this paper, we make two contributions to the field of level set based image segmentation. Firstly, we propose shape dissimilarity measures on the space of level set functions wh...
Daniel Cremers, Stanley Osher, Stefano Soatto
SDM
2008
SIAM
134views Data Mining» more  SDM 2008»
14 years 11 months ago
Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation
Covariate shift is a situation in supervised learning where training and test inputs follow different distributions even though the functional relation remains unchanged. A common...
Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen...