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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...
IESS
2007
Springer
165views Hardware» more  IESS 2007»
16 years 21 days ago
Data Reuse Driven Memory and Network-On-Chip Co-Synthesis
NoCs present a possible communication infrastructure solution to deal with increased design complexity and shrinking time-to-market. The communication infrastructure is a signific...
Ilya Issenin, Nikil Dutt
JCB
2006
185views more  JCB 2006»
15 years 6 months ago
A Probabilistic Methodology for Integrating Knowledge and Experiments on Biological Networks
Biological systems are traditionally studied by focusing on a specific subsystem, building an intuitive model for it, and refining the model using results from carefully designed ...
Irit Gat-Viks, Amos Tanay, Daniela Raijman, Ron Sh...
APNOMS
2006
Springer
15 years 10 months ago
"P4L": A Four Layers P2P Model for Optimizing Resources Discovery and Localization
Peer-to-Peer systems are based on the concept of resources localization and mutualization in dynamic context. In specific environment such as mobile networks, characterized by high...
Mourad Amad, Ahmed Meddahi
IPPS
1997
IEEE
15 years 10 months ago
Designing Efficient Distributed Algorithms Using Sampling Techniques
In this paper we show the power of sampling techniques in designing efficient distributed algorithms. In particular, we show that using sampling techniques, on some networks, sele...
Sanguthevar Rajasekaran, David S. L. Wei