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» Inference and Learning in Planning
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JMLR
2010
143views more  JMLR 2010»
14 years 11 months ago
Beware of the DAG!
Directed acyclic graph (DAG) models are popular tools for describing causal relationships and for guiding attempts to learn them from data. In particular, they appear to supply a ...
A. Philip Dawid
ICASSP
2011
IEEE
14 years 8 months ago
Cooperative prey herding based on diffusion adaptation
Mobile adaptive networks consist of a collection of nodes with learning and motion abilities that interact with each other locally in order to solve distributed processing and dis...
Sheng-Yuan Tu, Ali H. Sayed
CHI
2003
ACM
16 years 5 months ago
Ethnographic interviews guide design of ford vehicles website
This case study describes ethnographic interviews with vehicle buyers to learn how they make purchase decisions. The research was conducted for J. Walter Thompson (JWT), the digit...
Lori Anschuetz, Stephanie Rosenbaum
ICML
2005
IEEE
16 years 5 months ago
Bounded real-time dynamic programming: RTDP with monotone upper bounds and performance guarantees
MDPs are an attractive formalization for planning, but realistic problems often have intractably large state spaces. When we only need a partial policy to get from a fixed start s...
H. Brendan McMahan, Maxim Likhachev, Geoffrey J. G...
HAPTICS
2007
IEEE
15 years 11 months ago
The Effect of Virtual Haptic Training on Real Surgical Drilling Proficiency
This sketch presents the design and preliminary results of a study that investigates the transference of motor skills learned in a haptic-enabled virtual environment to performanc...
Christopher Sewell, Nikolas H. Blevins, Sumanth Pe...