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» On Weak Markov's Principle
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778views
15 years 5 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
KDD
2007
ACM
156views Data Mining» more  KDD 2007»
14 years 8 months ago
Estimating rates of rare events at multiple resolutions
We consider the problem of estimating occurrence rates of rare events for extremely sparse data, using pre-existing hierarchies to perform inference at multiple resolutions. In pa...
Deepak Agarwal, Andrei Z. Broder, Deepayan Chakrab...
SIGMOD
2007
ACM
192views Database» more  SIGMOD 2007»
14 years 7 months ago
Benchmarking declarative approximate selection predicates
Declarative data quality has been an active research topic. The fundamental principle behind a declarative approach to data quality is the use of declarative statements to realize...
Amit Chandel, Oktie Hassanzadeh, Nick Koudas, Moha...
SENSYS
2005
ACM
14 years 1 months ago
Intelligent light control using sensor networks
Increasing user comfort and reducing operation costs have always been two primary objectives of building operations and control strategies. Current building control strategies are...
Vipul Singhvi, Andreas Krause, Carlos Guestrin, Ja...
PROMAS
2004
Springer
14 years 27 days ago
Coordinating Teams in Uncertain Environments: A Hybrid BDI-POMDP Approach
Distributed partially observable Markov decision problems (POMDPs) have emerged as a popular decision-theoretic approach for planning for multiagent teams, where it is imperative f...
Ranjit Nair, Milind Tambe