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EXPERT
2006
84views more  EXPERT 2006»
14 years 10 months ago
Infrastructure for Engineered Emergence on Sensor/Actuator Networks
abstraction rules that hide the complexity of systems of components. We've begun this process in the domain of sensor/actuator network applications, observing that in manyappl...
Jacob Beal, Jonathan Bachrach
TMC
2010
130views more  TMC 2010»
14 years 8 months ago
SYNAPSE++: Code Dissemination in Wireless Sensor Networks Using Fountain Codes
—This paper presents SYNAPSE++, a system for over the air reprogramming of wireless sensor networks (WSNs). In contrast to previous solutions, which implement plain negative ackn...
Michele Rossi, Nicola Bui, Giovanni Zanca, Luca St...
ICML
1998
IEEE
15 years 10 months ago
Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting
In a recent paper, Friedman, Geiger, and Goldszmidt [8] introduced a classifier based on Bayesian networks, called Tree Augmented Naive Bayes (TAN), that outperforms naive Bayes a...
Moisés Goldszmidt, Nir Friedman, Thomas J. ...
POPL
2006
ACM
15 years 10 months ago
Engineering with logic: HOL specification and symbolic-evaluation testing for TCP implementations
The TCP/IP protocols and Sockets API underlie much of modern computation, but their semantics have historically been very complex and ill-defined. The real standard is the de fact...
Steve Bishop, Matthew Fairbairn, Michael Norrish, ...
JMLR
2008
230views more  JMLR 2008»
14 years 10 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...