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» Using model knowledge for learning inverse dynamics
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AIIA
2005
Springer
15 years 8 months ago
A Semantic Kernel to Exploit Linguistic Knowledge
Abstract. Improving accuracy in Information Retrieval tasks via semantic information is a complex problem characterized by three main aspects: the document representation model, th...
Roberto Basili, Marco Cammisa, Alessandro Moschitt...
ROBOCUP
2007
Springer
153views Robotics» more  ROBOCUP 2007»
15 years 8 months ago
Model-Based Reinforcement Learning in a Complex Domain
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
Shivaram Kalyanakrishnan, Peter Stone, Yaxin Liu
CORR
2007
Springer
144views Education» more  CORR 2007»
15 years 2 months ago
Distributing the Kalman Filter for Large-Scale Systems
This paper derives a near optimal distributed Kalman filter to estimate a large-scale random field monitored by a network of N sensors. The field is described by a sparsely con...
Usman A. Khan, José M. F. Moura
ICML
2009
IEEE
16 years 3 months ago
Herding dynamical weights to learn
A new "herding" algorithm is proposed which directly converts observed moments into a sequence of pseudo-samples. The pseudosamples respect the moment constraints and ma...
Max Welling
IDA
2003
Springer
15 years 7 months ago
Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing Dependencies
Abstract. Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any mode...
Allan Tucker, Xiaohui Liu