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» Learning Generative Models via Discriminative Approaches
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RECOMB
2002
Springer
14 years 8 months ago
From promoter sequence to expression: a probabilistic framework
We present a probabilistic framework that models the process by which transcriptional binding explains the mRNA expression of different genes. Our joint probabilistic model unifie...
Eran Segal, Yoseph Barash, Itamar Simon, Nir Fried...
SMA
1999
ACM
106views Solid Modeling» more  SMA 1999»
14 years 13 hour ago
Resolving non-uniqueness in design feature histories
Nearly all major commercial computer-aided design systems have adopted a feature-based design approach to solid modeling. Models are created via a sequence of operations which app...
Vincent A. Cicirello, William C. Regli
CIVR
2007
Springer
166views Image Analysis» more  CIVR 2007»
14 years 1 months ago
Multi-level local descriptor quantization for bag-of-visterms image representation
In the past, quantized local descriptors have been shown to be a good base for the representation of images, that can be applied to a wide range of tasks. However, current approac...
Pedro Quelhas, Jean-Marc Odobez
ICANN
2003
Springer
14 years 28 days ago
Sparse Coding with Invariance Constraints
We suggest a new approach to optimize the learning of sparse features under the constraints of explicit transformation symmetries imposed on the set of feature vectors. Given a set...
Heiko Wersing, Julian Eggert, Edgar Körner
IROS
2006
IEEE
146views Robotics» more  IROS 2006»
14 years 1 months ago
Adaptive Causal Models for Fault Diagnosis and Recovery in Multi-Robot Teams
— This paper presents an adaptive causal model method (adaptive CMM) for fault diagnosis and recovery in complex multi-robot teams. We claim that a causal model approach is effec...
Lynne E. Parker, Balajee Kannan