214 citations · 1.8k across the 88 of their papers we have counts for
Showing 2011 · stat.MLShow all
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stat.ML2011★ 1 cited
Entropy Search for Information-Efficient Global Optimization
Philipp Hennig, Christian J. Schuler
Contemporary global optimization algorithms are based on local measures of utility, rather than a probability measure over location and value of the optimum. They thus attempt to c…
stat.ML2011★ 41 cited
Gaussian Probabilities and Expectation Propagation
John P. Cunningham, Philipp Hennig, Simon Lacoste-Julien
While Gaussian probability densities are omnipresent in applied mathematics, Gaussian cumulative probabilities are hard to calculate in any but the univariate case. We study the ut…
stat.ML2011★ 10 cited
Optimal Reinforcement Learning for Gaussian Systems
Philipp Hennig
The exploration-exploitation trade-off is among the central challenges of reinforcement learning. The optimal Bayesian solution is intractable in general. This paper studies to wha…