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» Complexity of Max-SAT using stochastic algorithms
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116
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STOC
2004
ACM
150views Algorithms» more  STOC 2004»
16 years 2 months ago
Typical properties of winners and losers in discrete optimization
We present a probabilistic analysis for a large class of combinatorial optimization problems containing, e.g., all binary optimization problems defined by linear constraints and a...
René Beier, Berthold Vöcking
161
Voted
JMLR
2012
13 years 4 months ago
Multi Kernel Learning with Online-Batch Optimization
In recent years there has been a lot of interest in designing principled classification algorithms over multiple cues, based on the intuitive notion that using more features shou...
Francesco Orabona, Jie Luo, Barbara Caputo
ICANN
2005
Springer
15 years 7 months ago
CrySSMEx, a Novel Rule Extractor for Recurrent Neural Networks: Overview and Case Study
In this paper, it will be shown that it is feasible to extract finite state machines in a domain of, for rule extraction, previously unencountered complexity. The algorithm used i...
Henrik Jacobsson, Tom Ziemke
133
Voted
UAI
2008
15 years 3 months ago
CORL: A Continuous-state Offset-dynamics Reinforcement Learner
Continuous state spaces and stochastic, switching dynamics characterize a number of rich, realworld domains, such as robot navigation across varying terrain. We describe a reinfor...
Emma Brunskill, Bethany R. Leffler, Lihong Li, Mic...
125
Voted
WSC
2008
15 years 4 months ago
Multi-objective UAV mission planning using evolutionary computation
This investigation develops an innovative algorithm for multiple autonomous unmanned aerial vehicle (UAV) mission routing. The concept of a UAV Swarm Routing Problem (SRP) as a ne...
Adam J. Pohl, Gary B. Lamont