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DSP
2007
13 years 7 months ago
Variational and stochastic inference for Bayesian source separation
We tackle the general linear instantaneous model (possibly underdetermined and noisy) where we model the source prior with a Student t distribution. The conjugate-exponential char...
Ali Taylan Cemgil, Cédric Févotte, S...
ESOP
1994
Springer
13 years 11 months ago
Dimension Types
Scientists and engineers must ensure that physical equations are dimensionally consistent, but existing programming languages treat all numeric values as dimensionless. This paper ...
Andrew Kennedy
UAI
1997
13 years 8 months ago
Nonuniform Dynamic Discretization in Hybrid Networks
We consider probabilistic inference in general hybrid networks, which include continuous and discrete variables in an arbitrary topology. We reexamine the question of variable dis...
Alexander V. Kozlov, Daphne Koller
ESOP
2003
Springer
14 years 21 days ago
Type Error Slicing in Implicitly Typed Higher-Order Languages
Previous methods have generally identified the location of a type error as a particular program point or the program subtree rooted at that point. We present a new approach that ...
Christian Haack, J. B. Wells
EMNLP
2006
13 years 9 months ago
A Hybrid Markov/Semi-Markov Conditional Random Field for Sequence Segmentation
Markov order-1 conditional random fields (CRFs) and semi-Markov CRFs are two popular models for sequence segmentation and labeling. Both models have advantages in terms of the typ...
Galen Andrew