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» A Continuous Derivative for Real-Valued Functions
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ICML
2003
IEEE
14 years 8 months ago
Bayes Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
Yaakov Engel, Shie Mannor, Ron Meir
COCOS
2003
Springer
148views Optimization» more  COCOS 2003»
14 years 22 days ago
Convex Programming Methods for Global Optimization
We investigate some approaches to solving nonconvex global optimization problems by convex nonlinear programming methods. We assume that the problem becomes convex when selected va...
John N. Hooker
DASFAA
2007
IEEE
202views Database» more  DASFAA 2007»
14 years 1 months ago
Optimizing Moving Queries over Moving Object Data Streams
With the increasing in demand on location-based aware services and RFIDs, efficient processing of continuous queries over moving object streams becomes important. In this paper, w...
Dan Lin, Bin Cui, Dongqing Yang
TIP
1998
162views more  TIP 1998»
13 years 7 months ago
Variational image segmentation using boundary functions
Abstract—A general variational framework for image approximation and segmentation is introduced. By using a continuous “line-process” to represent edge boundaries, it is poss...
Gary A. Hewer, Charles S. Kenney, B. S. Manjunath
NIPS
2003
13 years 8 months ago
Gene Expression Clustering with Functional Mixture Models
We propose a functional mixture model for simultaneous clustering and alignment of sets of curves measured on a discrete time grid. The model is specifically tailored to gene exp...
Darya Chudova, Christopher E. Hart, Eric Mjolsness...