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» Optimized fixed-size kernel models for large data sets
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NIPS
2008
13 years 10 months ago
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
Shenghuo Zhu, Kai Yu, Yihong Gong
NIPS
2001
13 years 9 months ago
Quantizing Density Estimators
We suggest a nonparametric framework for unsupervised learning of projection models in terms of density estimation on quantized sample spaces. The objective is not to optimally re...
Peter Meinicke, Helge Ritter
IJRR
2010
102views more  IJRR 2010»
13 years 7 months ago
Space-carving Kernels for Accurate Rough Terrain Estimation
Abstract— Accurate terrain estimation is critical for autonomous offroad navigation. Reconstruction of a 3D surface allows rough and hilly ground to be represented, yielding fast...
Raia Hadsell, J. Andrew Bagnell, Daniel F. Huber, ...
IPPS
2010
IEEE
13 years 6 months ago
On the importance of bandwidth control mechanisms for scheduling on large scale heterogeneous platforms
We study three scheduling problems (file redistribution, independent tasks scheduling and broadcasting) on large scale heterogeneous platforms under the Bounded Multi-port Model. I...
Olivier Beaumont, Hejer Rejeb
FGR
2004
IEEE
159views Biometrics» more  FGR 2004»
14 years 5 days ago
Null Space-based Kernel Fisher Discriminant Analysis for Face Recognition
The null space-based LDA takes full advantage of the null space while the other methods remove the null space. It proves to be optimal in performance. From the theoretical analysi...
Wei Liu, Yunhong Wang, Stan Z. Li, Tieniu Tan