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» Online Learning of Approximate Dependency Parsing Algorithms
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SIAMMA
2011
97views more  SIAMMA 2011»
12 years 10 months ago
Convergence Rates for Greedy Algorithms in Reduced Basis Methods
The reduced basis method was introduced for the accurate online evaluation of solutions to a parameter dependent family of elliptic partial differential equations. ly, it can be ...
Peter Binev, Albert Cohen, Wolfgang Dahmen, Ronald...
EWSN
2004
Springer
14 years 7 months ago
Context-Aware Sensors
Wireless sensor networks typically consist of a large number of sensor nodes embedded in a physical space. Such sensors are low-power devices that are primarily used for monitoring...
Eiman Elnahrawy, Badri Nath
ML
2002
ACM
143views Machine Learning» more  ML 2002»
13 years 7 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
NIPS
2007
13 years 9 months ago
Agreement-Based Learning
The learning of probabilistic models with many hidden variables and nondecomposable dependencies is an important and challenging problem. In contrast to traditional approaches bas...
Percy Liang, Dan Klein, Michael I. Jordan
ICML
2008
IEEE
14 years 8 months ago
Sample-based learning and search with permanent and transient memories
We present a reinforcement learning architecture, Dyna-2, that encompasses both samplebased learning and sample-based search, and that generalises across states during both learni...
David Silver, Martin Müller 0003, Richard S. ...