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» Causal inference using the algorithmic Markov condition
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IROS
2006
IEEE
121views Robotics» more  IROS 2006»
15 years 3 months 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
BMCBI
2010
117views more  BMCBI 2010»
14 years 10 months ago
New decoding algorithms for Hidden Markov Models using distance measures on labellings
Background: Existing hidden Markov model decoding algorithms do not focus on approximately identifying the sequence feature boundaries. Results: We give a set of algorithms to com...
Daniel G. Brown 0001, Jakub Truszkowski
CIKM
2009
Springer
15 years 4 months ago
A social recommendation framework based on multi-scale continuous conditional random fields
This paper addresses the issue of social recommendation based on collaborative filtering (CF) algorithms. Social recommendation emphasizes utilizing various attributes informatio...
Xin Xin, Irwin King, Hongbo Deng, Michael R. Lyu
ICIP
2004
IEEE
15 years 11 months ago
A hidden markov model framework for traffic event detection using video features
We present a novel approach for highway traffic event detection. Our algorithm extracts features directly from the compressed video and automatically detects traffic events using ...
Xiaokun Li, Fatih Murat Porikli
AAAI
2012
13 years 5 days ago
Transportability of Causal Effects: Completeness Results
The study of transportability aims to identify conditions under which causal information learned from experiments can be reused in a different environment where only passive obser...
Elias Bareinboim, Judea Pearl