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NIPS
2003
13 years 9 months ago
Robustness in Markov Decision Problems with Uncertain Transition Matrices
Optimal solutions to Markov Decision Problems (MDPs) are very sensitive with respect to the state transition probabilities. In many practical problems, the estimation of those pro...
Arnab Nilim, Laurent El Ghaoui
VMV
2008
107views Visualization» more  VMV 2008»
13 years 9 months ago
Learning with Few Examples using a Constrained Gaussian Prior on Randomized Trees
Machine learning with few training examples always leads to over-fitting problems, whereas human individuals are often able to recognize difficult object categories from only one ...
Erik Rodner, Joachim Denzler
ICASSP
2008
IEEE
14 years 2 months ago
Minimum mean bayes risk error quantization of prior probabilities
Bayesian hypothesis testing is investigated when the prior probabilities of the hypotheses, taken as a random vector, must be quantized. Nearest neighbor and centroid conditions f...
Kush R. Varshney, Lav R. Varshney
IROS
2008
IEEE
165views Robotics» more  IROS 2008»
14 years 2 months ago
Probabilistic navigation in dynamic environment using Rapidly-exploring Random Trees and Gaussian processes
— The paper describes a navigation algorithm for dynamic, uncertain environment. Moving obstacles are supposed to move on typical patterns which are pre-learned and are represent...
Chiara Fulgenzi, Christopher Tay, Anne Spalanzani,...
ISAAC
2005
Springer
127views Algorithms» more  ISAAC 2005»
14 years 1 months ago
Decision Making Based on Approximate and Smoothed Pareto Curves
Abstract. We consider bicriteria optimization problems and investigate the relationship between two standard approaches to solving them: (i) computing the Pareto curve and (ii) the...
Heiner Ackermann, Alantha Newman, Heiko Rögli...