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» The complexity of stochastic sequences
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JMLR
2008
230views more  JMLR 2008»
15 years 6 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...
AIIA
2009
Springer
16 years 22 days ago
Relational Temporal Data Mining for Wireless Sensor Networks
Wireless sensor networks (WSNs) represent a typical domain where there are complex temporal sequences of events. In this paper we propose a relational framework to model and analys...
Teresa Maria Altomare Basile, Nicola Di Mauro, Ste...
CORR
2006
Springer
76views Education» more  CORR 2006»
15 years 6 months ago
Complexity Constrained Noise-Free CDMA: Optimal Power Distribution and Spectral Efficiency
The issue of multiuser cooperation in a complexity constrained noise-free CDMA channel is addressed. Multiuser cooperation is imperative if conventional demodulation is expected to...
Rodrigo de Miguel, Ralf R. Müller
WSC
1998
15 years 7 months ago
Input Modeling Tools for Complex Problems
A simulation model is composed of inputs and logic; the inputs represent the uncertainty or randomness in the system, while the logic determines how the system reacts to the uncer...
Barry L. Nelson, Michael Yamnitsky
BMCBI
2008
93views more  BMCBI 2008»
15 years 6 months ago
Homology modelling of protein-protein complexes: a simple method and its possibilities and limitations
Background: Structure-based computational methods are needed to help identify and characterize protein-protein complexes and their function. For individual proteins, the most succ...
Guillaume Launay, Thomas Simonson