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AIPS
2008
15 years 7 months ago
Fast Dynamic Scheduling of Disjunctive Temporal Constraint Networks through Incremental Compilation
Autonomous systems operating in real-world environments must plan, schedule, and execute missions while robustly adapting to uncertainty and disturbance. One way to mitigate the e...
Julie A. Shah, Brian C. Williams
JMLR
2008
230views more  JMLR 2008»
15 years 5 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...
ICALP
2009
Springer
16 years 9 days ago
Quasirandom Rumor Spreading: Expanders, Push vs. Pull, and Robustness
Abstract Randomized rumor spreading is an efficient protocol to distribute information in networks. Recently, a quasirandom version has been proposed and proven to work equally we...
Benjamin Doerr, Tobias Friedrich, Thomas Sauerwald
IUI
2006
ACM
15 years 11 months ago
Augmenting kitchen appliances with a shared context using knowledge about daily events
Networked appliances can simplify our lives, but interacting with them can be difficult in itself. KitchenSense is an early prototype of a networked kitchen full of sensors that u...
Chia-Hsun Jackie Lee, Leonardo Bonanni, José...
IFIP
2003
Springer
15 years 10 months ago
Power-Saving in Wi-Fi Hotspots: An Analytical Study
Wi-Fi hotspots are one of the most promising scenarios for mobile computing. In this scenario, a very limiting factor is the scarcity of mobile-device energetic resources. Both har...
Giuseppe Anastasi, Marco Conti, Enrico Gregori, An...