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» Model reduction of periodic systems: a lifting approach
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TASLP
2010
97views more  TASLP 2010»
13 years 3 months ago
Hierarchical Bayesian Language Models for Conversational Speech Recognition
Traditional n-gram language models are widely used in state-of-the-art large vocabulary speech recognition systems. This simple model suffers from some limitations, such as overfi...
Songfang Huang, Steve Renals
DAC
1998
ACM
14 years 9 months ago
A Mixed Nodal-Mesh Formulation for Efficient Extraction and Passive Reduced-Order Modeling of 3D Interconnects
As VLSI circuit speeds have increased, reliable chip and system design can no longer be performed without accurate threedimensional interconnect models. In this paper, we describe...
Nuno Alexandre Marques, Mattan Kamon, Jacob White,...
JAIR
2002
120views more  JAIR 2002»
13 years 8 months ago
Learning Geometrically-Constrained Hidden Markov Models for Robot Navigation: Bridging the Topological-Geometrical Gap
Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
Hagit Shatkay, Leslie Pack Kaelbling
NAACL
2007
13 years 10 months ago
First-Order Probabilistic Models for Coreference Resolution
Traditional noun phrase coreference resolution systems represent features only of pairs of noun phrases. In this paper, we propose a machine learning method that enables features ...
Aron Culotta, Michael L. Wick, Andrew McCallum
IJON
2000
71views more  IJON 2000»
13 years 8 months ago
Variable selection using neural-network models
In this paper we propose an approach to variable selection that uses a neural-network model as the tool to determine which variables are to be discarded. The method performs a bac...
Giovanna Castellano, Anna Maria Fanelli