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DAC
1997
ACM
15 years 4 months ago
Sequence Compaction for Probabilistic Analysis of Finite-State Machines
- The objective of this paper is to provide an effective technique for accurate modeling of the external input sequences that affect the behavior of Finite State Machines (FSMs). T...
Diana Marculescu, Radu Marculescu, Massoud Pedram
TOG
2008
79views more  TOG 2008»
14 years 11 months ago
Continuous model synthesis
We present a novel method for procedurally modeling large complex shapes. Our approach is general-purpose and takes as input any 3D polyhedral model provided by a user. The algori...
Paul Merrell, Dinesh Manocha
ICML
2002
IEEE
16 years 19 days ago
Cranking: Combining Rankings Using Conditional Probability Models on Permutations
A new approach to ensemble learning is introduced that takes ranking rather than classification as fundamental, leading to models on the symmetric group and its cosets. The approa...
Guy Lebanon, John D. Lafferty
IJON
2002
74views more  IJON 2002»
14 years 11 months ago
Optimal spontaneous activity in neural network modeling
We consider the origin of the high-dimensional input space as a variable which can be optimized before or during neuronal learning. This set of variables acts as a translation on ...
Daniel Remondini, Nathan Intrator, Gastone C. Cast...
ICMT
2009
Springer
15 years 6 months ago
Automatic Model Generation Strategies for Model Transformation Testing
Testing model transformations requires input models which are graphs of inter-connected objects that must conform to a meta-model and meta-constraints from heterogeneous sources su...
Sagar Sen, Benoit Baudry, Jean-Marie Mottu