67 search results - page 1 / 14 » A stochastic memoizer for sequence data |
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
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...
DCC
2010
IEEE
13 years 11 months ago
2010
IEEE
In this work we describe a sequence compression method based on combining a Bayesian nonparametric sequence model with entropy encoding. The model, a hierarchy of Pitman-Yor proce...
CACM
2011
12 years 12 months ago
2011
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...
ICPR
2002
IEEE
13 years 10 months ago
2002
IEEE
False matching due to errors in feature extraction and changes in illumination between frames may occur in feature tracking in image sequences. False matching leads to outliers in...
SIAMCO
2000
13 years 4 months ago
2000
We study almost-sure limiting properties, taken as 0, of the finite horizon sequence of random estimates { 0, 1, 2, . . . , T/ } for the linear stochastic gradient algorithm n+1 ...