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ATAL
2010
Springer
13 years 8 months ago
Preference elicitation for risky prospects
Minimax-regret preference elicitation allows intelligent decisions to be made on behalf of people facing risky choices. Standard gamble queries, a vital tool in this type of prefe...
Greg Hines, Kate Larson
GECCO
2008
Springer
186views Optimization» more  GECCO 2008»
13 years 8 months ago
A pareto following variation operator for fast-converging multiobjective evolutionary algorithms
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
A. K. M. Khaled Ahsan Talukder, Michael Kirley, Ra...
MM
2010
ACM
198views Multimedia» more  MM 2010»
13 years 7 months ago
Social pixels: genesis and evaluation
Huge amounts of social multimedia is being created daily by a combination of globally distributed disparate sensors, including human-sensors (e.g. tweets) and video cameras. Taken...
Vivek K. Singh, Mingyan Gao, Ramesh Jain
MOBICOM
2010
ACM
13 years 7 months ago
Bartendr: a practical approach to energy-aware cellular data scheduling
Cellular radios consume more power and suffer reduced data rate when the signal is weak. According to our measurements, the communication energy per bit can be as much as 6x highe...
Aaron Schulman, Vishnu Navda, Ramachandran Ramjee,...
AI
2007
Springer
13 years 7 months ago
Learning action models from plan examples using weighted MAX-SAT
AI planning requires the definition of action models using a formal action and plan description language, such as the standard Planning Domain Definition Language (PDDL), as inp...
Qiang Yang, Kangheng Wu, Yunfei Jiang