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ACL
2012
13 years 8 months ago
Pattern Learning for Relation Extraction with a Hierarchical Topic Model
We describe the use of a hierarchical topic model for automatically identifying syntactic and lexical patterns that explicitly state ontological relations. We leverage distant sup...
Enrique Alfonseca, Katja Filippova, Jean-Yves Delo...
IJHPCA
2007
88views more  IJHPCA 2007»
15 years 6 months ago
Performance Optimization and Modeling of Blocked Sparse Kernels
We present a method for automatically selecting optimal implementations of sparse matrixvector operations. Our software ‘AcCELS’ (Accelerated Compress-storage Elements for Lin...
Alfredo Buttari, Victor Eijkhout, Julien Langou, S...
NIPS
2007
15 years 7 months ago
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
198
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WSC
2001
15 years 7 months ago
Accounting for input model and parameter uncertainty in simulation
Taking into account input-model, input-parameter, and stochastic uncertainties inherent in many simulations, our Bayesian approach to input modeling yields valid point and confide...
Faker Zouaoui, James R. Wilson
CVPR
2009
IEEE
17 years 1 months ago
Recognising Action as Clouds of Space-Time Interest Points
Much of recent action recognition research is based on space-time interest points extracted from video using a Bag of Words (BOW) representation. It mainly relies on the discrimi...
Matteo Bregonzio (Queen Mary, University of London...