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AAAI
2012
13 years 9 months ago
Advances in Lifted Importance Sampling
We consider lifted importance sampling (LIS), a previously proposed approximate inference algorithm for statistical relational learning (SRL) models. LIS achieves substantial vari...
Vibhav Gogate, Abhay Kumar Jha, Deepak Venugopal
CORR
2012
Springer
171views Education» more  CORR 2012»
14 years 2 months ago
Random Feature Maps for Dot Product Kernels
Approximating non-linear kernels using feature maps has gained a lot of interest in recent years due to applications in reducing training and testing times of SVM classifiers and...
Purushottam Kar, Harish Karnick
AAAI
2012
13 years 9 months ago
Prediction and Fault Detection of Environmental Signals with Uncharacterised Faults
Many signals of interest are corrupted by faults of an unknown type. We propose an approach that uses Gaussian processes and a general “fault bucket” to capture a priori uncha...
Michael A. Osborne, Roman Garnett, Kevin Swersky, ...
IPMI
2005
Springer
16 years 7 months ago
Approximating Anatomical Brain Connectivity with Diffusion Tensor MRI Using Kernel-Based Diffusion Simulations
We present a new technique for noninvasively tracing brain white matter fiber tracts using diffusion tensor magnetic resonance imaging (DT-MRI). This technique is based on performi...
Jun Zhang, Ning Kang, Stephen E. Rose
ICML
2008
IEEE
16 years 7 months ago
ManifoldBoost: stagewise function approximation for fully-, semi- and un-supervised learning
We introduce a boosting framework to solve a classification problem with added manifold and ambient regularization costs. It allows for a natural extension of boosting into both s...
Nicolas Loeff, David A. Forsyth, Deepak Ramachandr...