87 search results - page 12 / 18 » Adaptive MCMC with Bayesian Optimization |
AAAI
2006
13 years 9 months ago
2006
My research attempts to address on-line action selection in reinforcement learning from a Bayesian perspective. The idea is to develop more effective action selection techniques b...
ICONIP
2007
13 years 9 months ago
2007
Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
TSP
2008
13 years 7 months ago
2008
The data of interest are assumed to be represented as N-dimensional real vectors, and these vectors are compressible in some linear basis B, implying that the signal can be recons...
AAAI
2011
12 years 7 months ago
2011
Utility elicitation is an important component of many applications, such as decision support systems and recommender systems. Such systems query users about their preferences and ...
ECCV
2002
Springer
14 years 9 months ago
2002
Springer
Sequential random sampling (`Markov Chain Monte-Carlo') is a popular strategy for many vision problems involving multimodal distributions over high-dimensional parameter spac...