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» Learning the Structure of Dynamic Probabilistic Networks
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JMLR
2010
137views more  JMLR 2010»
13 years 2 months ago
Importance Sampling for Continuous Time Bayesian Networks
A continuous time Bayesian network (CTBN) uses a structured representation to describe a dynamic system with a finite number of states which evolves in continuous time. Exact infe...
Yu Fan, Jing Xu, Christian R. Shelton
JPDC
2010
137views more  JPDC 2010»
13 years 6 months ago
Parallel exact inference on the Cell Broadband Engine processor
—We present the design and implementation of a parallel exact inference algorithm on the Cell Broadband Engine (Cell BE). Exact inference is a key problem in exploring probabilis...
Yinglong Xia, Viktor K. Prasanna
IROS
2009
IEEE
174views Robotics» more  IROS 2009»
14 years 2 months ago
Characterization and modeling of wireless channels for networked robotic and control systems - a comprehensive overview
— The goal of this paper is to serve as a reference for researchers in robotics and control that are interested in realistic modeling, theoretical analysis and simulation of wire...
Yasamin Mostofi, Alejandro Gonzalez-Ruiz, Alireza ...
BIRTHDAY
2005
Springer
14 years 1 months ago
Towards Comprehensive Computational Models for Plan-Based Control of Autonomous Robots
In this paper we present an overview of recent developments in the plan-based control of autonomous robots. We identify computational principles that enable autonomous robots to a...
Michael Beetz
ACL
2009
13 years 5 months ago
Unsupervised Multilingual Grammar Induction
We investigate the task of unsupervised constituency parsing from bilingual parallel corpora. Our goal is to use bilingual cues to learn improved parsing models for each language ...
Benjamin Snyder, Tahira Naseem, Regina Barzilay