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ESOP
2011
Springer
14 years 1 months ago
Measure Transformer Semantics for Bayesian Machine Learning
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Johannes Borgström, Andrew D. Gordon, Michael...
AAAI
2011
13 years 10 months ago
Learning Accuracy and Availability of Humans Who Help Mobile Robots
When mobile robots perform tasks in environments with humans, it seems appropriate for the robots to rely on such humans for help instead of dedicated human oracles or supervisors...
Stephanie Rosenthal, Manuela M. Veloso, Anind K. D...
NIPS
2001
14 years 11 months ago
Algorithmic Luckiness
Classical statistical learning theory studies the generalisation performance of machine learning algorithms rather indirectly. One of the main detours is that algorithms are studi...
Ralf Herbrich, Robert C. Williamson
COLT
2010
Springer
14 years 8 months ago
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradie...
John Duchi, Elad Hazan, Yoram Singer
DIGRA
2005
Springer
15 years 3 months ago
Learning Games as a Platform for Simulated Science Practice
In recent years, science education has been the focus of study and development of new gamebased learning environments. It has been argued that active and critical learning about r...
Rikke Magnussen