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» Learning a Generative Model for Structural Representations
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AIED
2009
Springer
15 years 9 months ago
From Conceptual Models to Agent-based Simulations: Why and How
The core problem we address in this paper is how to take a declarative conceptual representation of a complex system and produce an agent-based simulation of that model. In particu...
Swaroop Vattam, Ashok K. Goel, Spencer Rugaber, Ci...
132
Voted
IFIP3
1998
151views Education» more  IFIP3 1998»
15 years 3 months ago
Conceptual Workflow Modelling for Remote Courses
Development of a wide spread project intended to teaching Computer Science, integrating a considerable number of students all over a country with big geographical extension and sc...
José Palazzo M. de Oliveira, Mariano Nicola...
ICML
2007
IEEE
16 years 3 months ago
Dynamic hierarchical Markov random fields and their application to web data extraction
Hierarchical models have been extensively studied in various domains. However, existing models assume fixed model structures or incorporate structural uncertainty generatively. In...
Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen
COLT
1994
Springer
15 years 6 months ago
Learning Probabilistic Automata with Variable Memory Length
We propose and analyze a distribution learning algorithm for variable memory length Markov processes. These processes can be described by a subclass of probabilistic nite automata...
Dana Ron, Yoram Singer, Naftali Tishby
CORR
2011
Springer
222views Education» more  CORR 2011»
14 years 6 months ago
Weakly Supervised Learning of Foreground-Background Segmentation using Masked RBMs
Abstract. We propose an extension of the Restricted Boltzmann Machine (RBM) that allows the joint shape and appearance of foreground objects in cluttered images to be modeled indep...
Nicolas Heess, Nicolas Le Roux, John M. Winn