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» Incompleteness in a General Setting
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ICML
2000
IEEE
14 years 10 months ago
Convergence Problems of General-Sum Multiagent Reinforcement Learning
Stochastic games are a generalization of MDPs to multiple agents, and can be used as a framework for investigating multiagent learning. Hu and Wellman (1998) recently proposed a m...
Michael H. Bowling
ECRTS
2007
IEEE
14 years 4 months ago
The Global Feasibility and Schedulability of General Task Models on Multiprocessor Platforms
Feasibility analysis determines (prior to system execution-time) whether a specified collection of hard-realtime jobs executed on a processing platform can meet all deadlines. In...
Nathan Fisher, Sanjoy K. Baruah
PODS
2011
ACM
201views Database» more  PODS 2011»
13 years 20 days ago
Data exchange beyond complete data
In the traditional data exchange setting, source instances are restricted to be complete in the sense that every fact is either true or false in these instances. Although natural ...
Marcelo Arenas, Jorge Pérez, Juan L. Reutte...
AUSAI
2008
Springer
13 years 12 months ago
Learning to Find Relevant Biological Articles without Negative Training Examples
Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
Keith Noto, Milton H. Saier Jr., Charles Elkan
CIMAGING
2008
142views Hardware» more  CIMAGING 2008»
13 years 11 months ago
Greedy signal recovery and uncertainty principles
This paper seeks to bridge the two major algorithmic approaches to sparse signal recovery from an incomplete set of linear measurements
Deanna Needell, Roman Vershynin