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SODA
2010
ACM
190views Algorithms» more  SODA 2010»
14 years 3 months ago
One-Counter Markov Decision Processes
We study the computational complexity of some central analysis problems for One-Counter Markov Decision Processes (OC-MDPs), a class of finitely-presented, countable-state MDPs. O...
Tomas Brazdil, Vaclav Brozek, Kousha Etessami, Ant...
AAAI
2007
13 years 8 months ago
Acquiring Visibly Intelligent Behavior with Example-Guided Neuroevolution
Much of artificial intelligence research is focused on devising optimal solutions for challenging and well-defined but highly constrained problems. However, as we begin creating...
Bobby D. Bryant, Risto Miikkulainen
KDD
2004
ACM
196views Data Mining» more  KDD 2004»
14 years 6 months ago
Adversarial classification
Essentially all data mining algorithms assume that the datagenerating process is independent of the data miner's activities. However, in many domains, including spam detectio...
Nilesh N. Dalvi, Pedro Domingos, Mausam, Sumit K. ...
ALT
2005
Springer
14 years 2 months ago
Defensive Universal Learning with Experts
This paper shows how universal learning can be achieved with expert advice. To this aim, we specify an experts algorithm with the following characteristics: (a) it uses only feedba...
Jan Poland, Marcus Hutter
COCO
1994
Springer
140views Algorithms» more  COCO 1994»
13 years 10 months ago
Random Debaters and the Hardness of Approximating Stochastic Functions
A probabilistically checkable debate system (PCDS) for a language L consists of a probabilisticpolynomial-time veri er V and a debate between Player 1, who claims that the input x ...
Anne Condon, Joan Feigenbaum, Carsten Lund, Peter ...