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ACL
1994
15 years 5 months ago
A Markov Language Learning Model for Finite Parameter Spaces
This paper shows how to formally characterize language learning in a finite parameter space as a Markov structure, hnportant new language learning results follow directly: explici...
Partha Niyogi, Robert C. Berwick
PAMI
2008
161views more  PAMI 2008»
15 years 4 months ago
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models
The Expectation Maximization (EM) algorithm is widely used for learning finite mixture models despite its greedy nature. Most popular model-based clustering techniques might yield...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...
FGCS
2006
74views more  FGCS 2006»
15 years 4 months ago
A performance model of non-deterministic particle transport on large-scale systems
In this work we present a predictive analytical model that encompasses the performance and scaling characteristics of a nondeterministic particle transport application, MCNP (Mont...
Mark M. Mathis, Darren J. Kerbyson, Adolfy Hoisie
UIST
1995
ACM
15 years 8 months ago
Visual Interfaces for Solids Modeling
This paper exploresthe useof visualoperatorsfor solidsmodeling. We focus on designing interfaces for free-form operators such as blends, sweeps, and deformations, because these op...
Cindy Grimm, David Pugmire
BMCBI
2007
179views more  BMCBI 2007»
15 years 4 months ago
Automated smoother for the numerical decoupling of dynamics models
Background: Structure identification of dynamic models for complex biological systems is the cornerstone of their reverse engineering. Biochemical Systems Theory (BST) offers a pa...
Marco Vilela, Carlos Cristiano H. Borges, Susana V...