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NIPS
2008
15 years 8 months ago
On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization
This work characterizes the generalization ability of algorithms whose predictions are linear in the input vector. To this end, we provide sharp bounds for Rademacher and Gaussian...
Sham M. Kakade, Karthik Sridharan, Ambuj Tewari
OPODIS
2008
15 years 8 months ago
Impact of Information on the Complexity of Asynchronous Radio Broadcasting
We consider asynchronous deterministic broadcasting in radio networks. An execution of a broadcasting protocol is a series of events, each of which consists of simultaneous transm...
Tiziana Calamoneri, Emanuele G. Fusco, Andrzej Pel...
LWA
2007
15 years 8 months ago
Taking the Teacher's Perspective for User Modeling in Complex Domains
Serious games that should adapt training to the individual might benefit from methods that are developed for intelligent tutoring systems. One method, model tracing, might be used...
Christian P. Janssen, Hedderik van Rijn
NIPS
2007
15 years 8 months ago
Discovering Weakly-Interacting Factors in a Complex Stochastic Process
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
Charlie Frogner, Avi Pfeffer
VAMOS
2008
Springer
15 years 8 months ago
How complex is my Product Line? The case for Variation Point Metrics
Software Product Lines aim at capturing the variability and commonality of a family of related programs that share a common set of assets. Variation points capture variability on ...
Roberto E. Lopez-Herrejon, Salvador Trujillo