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NIPS
2004
15 years 5 months ago
Log-concavity Results on Gaussian Process Methods for Supervised and Unsupervised Learning
Log-concavity is an important property in the context of optimization, Laplace approximation, and sampling; Bayesian methods based on Gaussian process priors have become quite pop...
Liam Paninski
CORR
2007
Springer
73views Education» more  CORR 2007»
15 years 4 months ago
Universal Reinforcement Learning
—We consider an agent interacting with an unmodeled environment. At each time, the agent makes an observation, takes an action, and incurs a cost. Its actions can influence futu...
Vivek F. Farias, Ciamac Cyrus Moallemi, Tsachy Wei...
CAD
2000
Springer
15 years 4 months ago
Lessons learned developing protocols for the industrial virtual enterprise
The protocols selected and developed by the NIIIP Consortium have been validated in three end-of-cycle demonstrations. In each cycle, a team with expertise in technical product da...
Martin Hardwick, K. C. Morris, David L. Spooner, T...
ICML
2009
IEEE
16 years 5 months ago
Approximate inference for planning in stochastic relational worlds
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Tobias Lang, Marc Toussaint
ICML
2006
IEEE
16 years 5 months ago
Kernelizing the output of tree-based methods
We extend tree-based methods to the prediction of structured outputs using a kernelization of the algorithm that allows one to grow trees as soon as a kernel can be defined on the...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...