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ECML
1993
Springer
14 years 21 days ago
Complexity Dimensions and Learnability
In machine learning theory, problem classes are distinguished because of di erences in complexity. In 6 , a stochastic model of learning from examples was introduced. This PAClear...
Shan-Hwei Nienhuys-Cheng, Mark Polman
IJCAI
2003
13 years 10 months ago
Simultaneous Adversarial Multi-Robot Learning
Multi-robot learning faces all of the challenges of robot learning with all of the challenges of multiagent learning. There has been a great deal of recent research on multiagent ...
Michael H. Bowling, Manuela M. Veloso
JAIR
2008
120views more  JAIR 2008»
13 years 8 months ago
Anytime Induction of Low-cost, Low-error Classifiers: a Sampling-based Approach
Machine learning techniques are gaining prevalence in the production of a wide range of classifiers for complex real-world applications with nonuniform testing and misclassificati...
Saher Esmeir, Shaul Markovitch
INFOCOM
2010
IEEE
13 years 7 months ago
Cross-layer Optimization for Wireless Networks with Deterministic Channel Models
Abstract—Existing work on cross-layer optimization for wireless networks adopts simple physical-layer models, i.e., treating interference as noise. In this paper, we adopt a dete...
Ziyu Shao, Minghua Chen, Salman Avestimehr, Shuo-Y...
CSE
2012
IEEE
12 years 4 months ago
Accelerating Quantum Monte Carlo Simulations of Real Materials on GPU Clusters
—Continuum quantum Monte Carlo (QMC) has proved to be an invaluable tool for predicting the properties of matter from fundamental principles. By solving the manybody Schr¨odinge...
Kenneth Esler, Jeongnim Kim, David M. Ceperley, Lu...