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NIPS
2008
15 years 8 months ago
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data
Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...
UAI
2000
15 years 8 months ago
Utilities as Random Variables: Density Estimation and Structure Discovery
Decision theory does not traditionally include uncertainty over utility functions. We argue that the a person's utility value for a given outcome can be treated as we treat o...
Urszula Chajewska, Daphne Koller
TNN
1998
146views more  TNN 1998»
15 years 6 months ago
An analytical framework for local feedforward networks
Interference in neural networks occurs when learning in one area of the input space causes unlearning in another area. Networks that are less susceptible to interference are refer...
S. Weaver, L. Baird, Marios M. Polycarpou
ITICSE
2009
ACM
16 years 1 months ago
First experiences with a classroom recording system
This paper describes our experiences with the first partial deployment of Presentations Automatically Organized from Lectures (PAOL), a lecture recording system developed and tes...
Paul E. Dickson, W. Richards Adrion, Allen R. Hans...
IROS
2006
IEEE
121views Robotics» more  IROS 2006»
16 years 24 days ago
Planning and Acting in Uncertain Environments using Probabilistic Inference
— An important problem in robotics is planning and selecting actions for goal-directed behavior in noisy uncertain environments. The problem is typically addressed within the fra...
Deepak Verma, Rajesh P. N. Rao