Probabilistic machine learning and artificial intelligence
@article{Ghahramani2015ProbabilisticML, title={Probabilistic machine learning and artificial intelligence}, author={Zoubin Ghahramani}, journal={Nature}, year={2015}, volume={521}, pages={452-459} }
How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and… CONTINUE READING
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References
SHOWING 1-10 OF 135 REFERENCES
Model-based machine learning
- Computer Science, Medicine
- Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
- 2013
- 116
- PDF
Machine learning - a probabilistic perspective
- Computer Science
- Adaptive computation and machine learning series
- 2012
- 5,773
- PDF
Practical Bayesian Optimization of Machine Learning Algorithms
- Computer Science, Mathematics
- NIPS
- 2012
- 3,543
- PDF
How to Grow a Mind: Statistics, Structure, and Abstraction
- Computer Science, Medicine
- Science
- 2011
- 1,120
- PDF
Gaussian Processes for Machine Learning
- Computer Science
- Adaptive computation and machine learning
- 2009
- 13,465
- PDF