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JMLR
2008
159views more  JMLR 2008»
13 years 9 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
14 years 1 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
14 years 3 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»
14 years 9 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
14 years 10 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