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JMLR
2008
159views more  JMLR 2008»
15 years 3 months ago
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies
When monitoring spatial phenomena, which can often be modeled as Gaussian processes (GPs), choosing sensor locations is a fundamental task. There are several common strategies to ...
Andreas Krause, Ajit Paul Singh, Carlos Guestrin
FSTTCS
2006
Springer
15 years 6 months ago
Normal and Feature Approximations from Noisy Point Clouds
We consider the problem of approximating normal and feature sizes of a surface from point cloud data that may be noisy. These problems are central to many applications dealing wit...
Tamal K. Dey, Jian Sun
HRI
2006
ACM
15 years 9 months ago
FOCUS: a generalized method for object discovery for robots that observe and interact with humans
The essence of the signal-to-symbol problem consists of associating a symbolic description of an object (e.g., a chair) to a signal (e.g., an image) that captures the real object....
Manuela M. Veloso, Paul E. Rybski, Felix von Hunde...
SIGMOD
2009
ACM
215views Database» more  SIGMOD 2009»
16 years 3 months ago
Efficient type-ahead search on relational data: a TASTIER approach
Existing keyword-search systems in relational databases require users to submit a complete query to compute answers. Often users feel "left in the dark" when they have l...
Guoliang Li, Shengyue Ji, Chen Li, Jianhua Feng
ICML
1996
IEEE
16 years 3 months ago
Discretizing Continuous Attributes While Learning Bayesian Networks
We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
Moisés Goldszmidt, Nir Friedman