Algorithms At Large: Publications
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[1]
Bayesian Multi−Scale Optimistic Optimization
Ziyu Wang‚ Babak Shakibi‚ Lin Jin and Nando de Freitas
In Artificial Intelligence and Statistics (AISTATS). Pages 1005−1014. 2014.
Details about Bayesian Multi−Scale Optimistic Optimization | BibTeX data for Bayesian Multi−Scale Optimistic Optimization | Download (pdf) of Bayesian Multi−Scale Optimistic Optimization
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[2]
Linear and Parallel Learning for Markov Random Fields
Yariv Dror Mizrahi‚ Misha Denil and Nando de Freitas
In International Conference on Machine Learning (ICML). 2014.
Details about Linear and Parallel Learning for Markov Random Fields | BibTeX data for Linear and Parallel Learning for Markov Random Fields | Download (pdf) of Linear and Parallel Learning for Markov Random Fields
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[3]
Herded Gibbs Sampling
Luke Bornn‚ Yutian Chen‚ Nando de Freitas‚ Mareija Eskelin‚ Jing Fang and Max Welling
In International Conference on Learning Representations (ICLR). 2013.
Details about Herded Gibbs Sampling | BibTeX data for Herded Gibbs Sampling | Link to Herded Gibbs Sampling
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[4]
Consistency of Online Random Forests
Misha Denil‚ David Matheson and Nando de Freitas
In International Conference on Machine Learning (ICML). Pages 1256–−1264. 2013.
JMLR &CPW 28 (3): 1256–1264‚ 2013
Details about Consistency of Online Random Forests | BibTeX data for Consistency of Online Random Forests | Download (pdf) of Consistency of Online Random Forests
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[5]
Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations
Nando de Freitas‚ Alex Smola and Masrour Zoghi
In International Conference on Machine Learning (ICML). 2012.
Details about Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations | BibTeX data for Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations | Link to Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations
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[6]
An Introduction to MCMC for Machine Learning
Christophe Andrieu‚ Nando de Freitas‚ Arnaud Doucet and Michael I. Jordan
In Machine Learning. Vol. 50. No. 1−2. Pages 5−43. 2003.
Details about An Introduction to MCMC for Machine Learning | BibTeX data for An Introduction to MCMC for Machine Learning | DOI (10.1023/A:1020281327116) | Link to An Introduction to MCMC for Machine Learning