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» Modeling Problem Transformations based on Data Complexity
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AAAI
2008
15 years 9 months ago
Maximum Entropy Inverse Reinforcement Learning
Recent research has shown the benefit of framing problems of imitation learning as solutions to Markov Decision Problems. This approach reduces learning to the problem of recoveri...
Brian Ziebart, Andrew L. Maas, J. Andrew Bagnell, ...
RECOMB
2006
Springer
16 years 7 months ago
Phylogenetic Profiling of Insertions and Deletions in Vertebrate Genomes
Micro-indels are small insertion or deletion events (indels) that occur during genome evolution. The study of micro-indels is important, both in order to better understand the unde...
Sagi Snir, Lior Pachter
CORR
2010
Springer
169views Education» more  CORR 2010»
15 years 1 months ago
Recommender Systems by means of Information Retrieval
In this paper we present a method for reformulating the Recommender Systems problem in an Information Retrieval one. In our tests we have a dataset of users who give ratings for s...
Alberto Costa, Fabio Roda
MIA
2010
170views more  MIA 2010»
15 years 1 months ago
Linear intensity-based image registration by Markov random fields and discrete optimization
We propose a framework for intensity-based registration of images by linear transformations, based on a discrete Markov Random Field (MRF) formulation. Here, the challenge arises ...
Darko Zikic, Ben Glocker, Oliver Kutter, Martin Gr...
SC
2005
ACM
16 years 8 days ago
Bridging the Macro and Micro: A Computing Intensive Earthquake Study Using Discovery Net
We present the development and use of a novel distributed geohazard modeling environment for the analysis and interpretation of large scale earthquake data sets. Our work demonstr...
Yike Guo, Jian Guo Liu, Moustafa Ghanem, Kyran Mis...