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ACL
1994
15 years 2 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
118
Voted
PAMI
2008
161views more  PAMI 2008»
15 years 19 days 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 21 days 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
82
Voted
UIST
1995
ACM
15 years 4 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 24 days 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...