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JMLR
2008
230views more  JMLR 2008»
13 years 8 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
PE
2002
Springer
176views Optimization» more  PE 2002»
13 years 7 months ago
Effective bandwidth estimation and testing for Markov sources
This work addresses the resource sharing problem in broadband communication networks that can guarantee some quality of service (QoS), and develops some results about data source ...
Juan Pechiar, Gonzalo Perera, María Simon
MOBIHOC
2010
ACM
13 years 5 months ago
On quality of monitoring for multi-channel wireless infrastructure networks
Passive monitoring utilizing distributed wireless sniffers is an effective technique to monitor activities in wireless infrastructure networks for fault diagnosis, resource manage...
Arun Chhetri, Huy Anh Nguyen, Gabriel Scalosub, Ro...
TASLP
2010
157views more  TASLP 2010»
13 years 2 months ago
HMM-Based Reconstruction of Unreliable Spectrographic Data for Noise Robust Speech Recognition
This paper presents a framework for efficient HMM-based estimation of unreliable spectrographic speech data. It discusses the role of Hidden Markov Models (HMMs) during minimum mea...
Bengt J. Borgstrom, Abeer Alwan
EMSOFT
2001
Springer
14 years 14 days ago
Interface Theories for Component-Based Design
Abstract. We classify component-based models of computation into component models and interface models. A component model speci es for each component how the component behaves in a...
Luca de Alfaro, Thomas A. Henzinger