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» Terminating Decision Algorithms Optimally
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145
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ML
2008
ACM
101views Machine Learning» more  ML 2008»
15 years 3 months ago
On reoptimizing multi-class classifiers
Significant changes in the instance distribution or associated cost function of a learning problem require one to reoptimize a previously-learned classifier to work under new cond...
Chris Bourke, Kun Deng, Stephen D. Scott, Robert E...
134
Voted
ICS
2010
Tsinghua U.
16 years 1 months ago
Distribution-Specific Agnostic Boosting
We consider the problem of boosting the accuracy of weak learning algorithms in the agnostic learning framework of Haussler (1992) and Kearns et al. (1992). Known algorithms for t...
Vitaly Feldman
116
Voted
SIROCCO
2008
15 years 5 months ago
Locating and Repairing Faults in a Network with Mobile Agents
Abstract. We consider a fixed, undirected, known network and a number of "mobile agents" which can traverse the network in synchronized steps. Some nodes in the network m...
Colin Cooper, Ralf Klasing, Tomasz Radzik
134
Voted
GECCO
2007
Springer
179views Optimization» more  GECCO 2007»
15 years 9 months ago
The second harmonic generation case-study as a gateway for es to quantum control problems
The Second Harmonic Generation (SHG), a process that turns out to be a good test case in the physics lab, can also be considered as a fairly simple theoretical test function for g...
Ofer M. Shir, Thomas Bäck
141
Voted
PLDI
2003
ACM
15 years 9 months ago
Points-to analysis using BDDs
This paper reports on a new approach to solving a subset-based points-to analysis for Java using Binary Decision Diagrams (BDDs). In the model checking community, BDDs have been s...
Marc Berndl, Ondrej Lhoták, Feng Qian, Laur...