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AAAI
2012
11 years 11 months ago
2012
This paper concerns learning and prediction with probabilistic models where the domain sizes of latent variables have no a priori upper-bound. Current approaches represent prior d...
NIPS
2008
13 years 10 months ago
2008
Compressive Sensing (CS) combines sampling and compression into a single subNyquist linear measurement process for sparse and compressible signals. In this paper, we extend the th...
IPMI
1999
Springer
14 years 10 months ago
1999
Springer
Inspired by the discussion in neurological research about the callosal fiber connections with respect to brain asymmetry we developed a technique that measures distances between br...
SMA
1993
ACM
14 years 1 months ago
1993
ACM
: Parametric design is an important modeling paradigm in computer aided design. Relationships (constraints) between the degrees of freedom (DOFs) of the model, instead of the DOFs ...
ICMI
2010
Springer
13 years 7 months ago
2010
Springer
Traditionally listener response prediction models are learned from pre-recorded dyadic interactions. Because of individual differences in behavior, these recordings do not capture...