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CACM
2011
120views more  CACM 2011»
14 years 4 months ago
The sequence memoizer
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
Frank Wood, Jan Gasthaus, Cédric Archambeau...
ICA
2007
Springer
15 years 1 months ago
Conjugate Gamma Markov Random Fields for Modelling Nonstationary Sources
In modelling nonstationary sources, one possible strategy is to define a latent process of strictly positive variables to model variations in second order statistics of the underly...
Ali Taylan Cemgil, Onur Dikmen
VR
2009
IEEE
228views Virtual Reality» more  VR 2009»
15 years 4 months ago
Natural Eye Motion Synthesis by Modeling Gaze-Head Coupling
Due to the intrinsic subtlety and dynamics of eye movements, automated generation of natural and engaging eye motion has been a challenging task for decades. In this paper we pres...
Xiaohan Ma, Zhigang Deng
NIPS
2007
14 years 11 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...
PERVASIVE
2006
Springer
14 years 9 months ago
Building Reliable Activity Models Using Hierarchical Shrinkage and Mined Ontology
Abstract. Activity inference based on object use has received considerable recent attention. Such inference requires statistical models that map activities to the objects used in p...
Emmanuel Munguia Tapia, Tanzeem Choudhury, Matthai...