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» Scale-Time Kernels and Models
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ICML
2002
IEEE
14 years 9 months ago
Learning the Kernel Matrix with Semi-Definite Programming
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
VRCAI
2004
ACM
14 years 2 months ago
Explorative construction of virtual worlds: an interactive kernel approach
Despite steady research advances in many aspects of virtual reality, building and testing virtual worlds remains to be a very difficult process. Most virtual environments are stil...
Jinseok Seo, Gerard Jounghyun Kim
TC
2010
13 years 7 months ago
Scalable Node-Level Computation Kernels for Parallel Exact Inference
—In this paper, we investigate data parallelism in exact inference with respect to arbitrary junction trees. Exact inference is a key problem in exploring probabilistic graphical...
Yinglong Xia, Viktor K. Prasanna
COMCOM
2004
96views more  COMCOM 2004»
13 years 8 months ago
Achieving proportional delay differentiation efficiently
In this paper, we focus on efficiently achieving Proportional Delay Differentiation (PDD), an instance of the Proportional Differentiation Model (PDM) first proposed under the Dif...
Hoon-Tong Ngin, Chen-Khong Tham
ICDM
2009
IEEE
163views Data Mining» more  ICDM 2009»
14 years 3 months ago
Kernel Conditional Quantile Estimation via Reduction Revisited
Quantile regression refers to the process of estimating the quantiles of a conditional distribution and has many important applications within econometrics and data mining, among ...
Novi Quadrianto, Kristian Kersting, Mark D. Reid, ...