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» Exploiting Deep Structure
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ICML
2009
IEEE
16 years 7 months ago
Partial order embedding with multiple kernels
We consider the problem of embedding arbitrary objects (e.g., images, audio, documents) into Euclidean space subject to a partial order over pairwise distances. Partial order cons...
Brian McFee, Gert R. G. Lanckriet
ICML
2005
IEEE
16 years 7 months ago
Near-optimal sensor placements in Gaussian processes
When monitoring spatial phenomena, which are often modeled as Gaussian Processes (GPs), choosing sensor locations is a fundamental task. A common strategy is to place sensors at t...
Carlos Guestrin, Andreas Krause, Ajit Paul Singh
ICML
2001
IEEE
16 years 7 months ago
Continuous-Time Hierarchical Reinforcement Learning
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
Mohammad Ghavamzadeh, Sridhar Mahadevan
ISBI
2002
IEEE
16 years 7 months ago
Capturing contextual dependencies in medical imagery using hierarchical multi-scale models
In this paper we summarize our results for two classes of hierarchical multi-scale models that exploit contextual information for detection of structure in mammographic imagery. T...
Paul Sajda, Clay Spence, Lucas C. Parra
ISBI
2006
IEEE
16 years 7 months ago
Image reconstruction strategies using dual modality MRI-NIR data
An imaging system which simultaneously performs near infrared (NIR) tomography and magnetic resonance imaging (MRI) has been developed at Dartmouth College, to study breast tissue...
Hamid Dehghani, Brian W. Pogue, Ben Brooksby, Subh...