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» A Framework for Multiple-Instance Learning
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EMNLP
2008
15 years 5 months ago
Learning with Probabilistic Features for Improved Pipeline Models
We present a novel learning framework for pipeline models aimed at improving the communication between consecutive stages in a pipeline. Our method exploits the confidence scores ...
Razvan C. Bunescu
ICONIP
2007
15 years 5 months ago
Finding Exploratory Rewards by Embodied Evolution and Constrained Reinforcement Learning in the Cyber Rodents
The aim of the Cyber Rodent project [1] is to elucidate the origin of our reward and affective systems by building artificial agents that share the natural biological constraints...
Eiji Uchibe, Kenji Doya
ESANN
2006
15 years 5 months ago
Learning for stochastic dynamic programming
Abstract. We present experimental results about learning function values (i.e. Bellman values) in stochastic dynamic programming (SDP). All results come from openDP (opendp.sourcef...
Sylvain Gelly, Jérémie Mary, Olivier...
NIPS
2003
15 years 5 months ago
Ambiguous Model Learning Made Unambiguous with 1/f Priors
What happens to the optimal interpretation of noisy data when there exists more than one equally plausible interpretation of the data? In a Bayesian model-learning framework the a...
Gurinder S. Atwal, William Bialek
NIPS
2000
15 years 5 months ago
Learning and Tracking Cyclic Human Motion
We present methods for learning and tracking human motion in video. We estimate a statistical model of typical activities from a large set of 3D periodic human motion data by segm...
Dirk Ormoneit, Hedvig Sidenbladh, Michael J. Black...