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» Learning Optimal Parameters in Decision-Theoretic Rough Sets
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CVPR
2009
IEEE
15 years 3 months ago
A Revisit of Generative Model for Automatic Image Annotation using Markov Random Fields
Much research effort on Automatic Image Annotation (AIA) has been focused on Generative Model, due to its well formed theory and competitive performance as compared with many we...
Yu Xiang (Fudan University), Xiangdong Zhou (Fudan...
ICPR
2006
IEEE
14 years 9 months ago
Part-Based Probabilistic Point Matching
Correspondence algorithms typically struggle with shapes that display part-based variation. We present a probabilistic approach that matches shapes using independent part transfor...
Graham McNeill, Sethu Vijayakumar
CORR
2010
Springer
143views Education» more  CORR 2010»
13 years 5 months ago
The Non-Bayesian Restless Multi-Armed Bandit: a Case of Near-Logarithmic Regret
In the classic Bayesian restless multi-armed bandit (RMAB) problem, there are N arms, with rewards on all arms evolving at each time as Markov chains with known parameters. A play...
Wenhan Dai, Yi Gai, Bhaskar Krishnamachari, Qing Z...
SIGECOM
2010
ACM
183views ECommerce» more  SIGECOM 2010»
14 years 1 months ago
The unavailable candidate model: a decision-theoretic view of social choice
One of the fundamental problems in the theory of social choice is aggregating the rankings of a set of agents (or voters) into a consensus ranking. Rank aggregation has found appl...
Tyler Lu, Craig Boutilier
ATAL
2005
Springer
14 years 2 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson