Corpus ID: 67787678

# Online Sampling from Log-Concave Distributions

@inproceedings{Lee2019OnlineSF,
title={Online Sampling from Log-Concave Distributions},
author={Holden Lee and Oren Mangoubi and N. Vishnoi},
booktitle={NeurIPS},
year={2019}
}
• Published in NeurIPS 2019
• Computer Science, Mathematics
• Given a sequence of convex functions $f_0, f_1, \ldots, f_T$, we study the problem of sampling from the Gibbs distribution $\pi_t \propto e^{-\sum_{k=0}^tf_k}$ for each epoch $t$ in an online manner. Interest in this problem derives from applications in machine learning, Bayesian statistics, and optimization where, rather than obtaining all the observations at once, one constantly acquires new data, and must continuously update the distribution. Our main result is an algorithm that generates… CONTINUE READING
5 Citations

#### References

SHOWING 1-10 OF 44 REFERENCES
Log-concave sampling: Metropolis-Hastings algorithms are fast!
• Mathematics, Computer Science
• COLT
• 2018
• 92
• PDF
Efficient Sampling from Time-Varying Log-Concave Distributions
• Computer Science, Mathematics
• J. Mach. Learn. Res.
• 2017
• 27
• PDF
Logarithmic regret algorithms for online convex optimization
• Mathematics, Computer Science
• Machine Learning
• 2007
• 794
• PDF
Coresets for Scalable Bayesian Logistic Regression
• Computer Science, Mathematics
• NIPS
• 2016
• 101
• PDF
Logistic Regression: The Importance of Being Improper
• Computer Science, Mathematics
• COLT
• 2018
• 24
• PDF
Minibatch Gibbs Sampling on Large Graphical Models
• Computer Science, Mathematics
• ICML
• 2018
• 11
• PDF