95 search results - page 12 / 19 » Learning Non-Stationary Dynamic Bayesian Networks |
IJCAI
2003
13 years 10 months ago
2003
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
CL
2000
Springer
14 years 1 months ago
2000
Springer
In this paper I give a brief overview of recent work on uncertainty inAI, and relate it to logical representations. Bayesian decision theory and logic are both normative frameworks...
NIPS
1998
13 years 10 months ago
1998
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
ICML
2004
IEEE
14 years 9 months ago
2004
IEEE
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
ICANNGA
2009
Springer
14 years 3 months ago
2009
Springer
We propose a generalized model with configurable discretizer actuators as a solution to the problem of the discretization of massive numerical datasets. Our solution is based on a ...