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ICML
2009
IEEE
16 years 3 months ago
Approximate inference for planning in stochastic relational worlds
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Tobias Lang, Marc Toussaint
107
Voted
ICML
2007
IEEE
16 years 3 months ago
On the value of pairwise constraints in classification and consistency
In this paper we consider the problem of classification in the presence of pairwise constraints, which consist of pairs of examples as well as a binary variable indicating whether...
Jian Zhang, Rong Yan
116
Voted
ICML
2003
IEEE
16 years 3 months ago
Learning with Knowledge from Multiple Experts
The use of domain knowledge in a learner can greatly improve the models it produces. However, high-quality expert knowledge is very difficult to obtain. Traditionally, researchers...
Matthew Richardson, Pedro Domingos
135
Voted
ICML
1998
IEEE
16 years 3 months ago
RL-TOPS: An Architecture for Modularity and Re-Use in Reinforcement Learning
This paper introduces the RL-TOPs architecture for robot learning, a hybrid system combining teleo-reactive planning and reinforcement learning techniques. The aim of this system ...
Malcolm R. K. Ryan, Mark D. Pendrith
120
Voted
ISBI
2008
IEEE
16 years 3 months ago
Deconvolution of confocal microscopy images using proximal iteration and sparse representations
We propose a deconvolution algorithm for images blurred and degraded by a Poisson noise. The algorithm uses a fast proximal backward-forward splitting iteration. This iteration mi...
François-Xavier Dupé, Mohamed-Jalal ...