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IJCAI
2007
13 years 10 months ago
Learning from Partial Observations
We present a general machine learning framework for modelling the phenomenon of missing information in data. We propose a masking process model to capture the stochastic nature of...
Loizos Michael
TIP
1998
129views more  TIP 1998»
13 years 8 months ago
Minimax partial distortion competitive learning for optimal codebook design
— The design of the optimal codebook for a given codebook size and input source is a challenging puzzle that remains to be solved. The key problem in optimal codebook design is h...
Ce Zhu, Lai-Man Po
ICRA
2009
IEEE
137views Robotics» more  ICRA 2009»
14 years 3 months ago
Unsupervised learning of 3D object models from partial views
— We present an algorithm for learning 3D object models from partial object observations. The input to our algorithm is a sequence of 3D laser range scans. Models learned from th...
Michael Ruhnke, Bastian Steder, Giorgio Grisetti, ...
ECML
2005
Springer
14 years 2 months ago
Active Learning in Partially Observable Markov Decision Processes
This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...
Robin Jaulmes, Joelle Pineau, Doina Precup
JAIR
2008
148views more  JAIR 2008»
13 years 8 months ago
Learning Partially Observable Deterministic Action Models
We present exact algorithms for identifying deterministic-actions' effects and preconditions in dynamic partially observable domains. They apply when one does not know the ac...
Eyal Amir, Allen Chang