accepted papers at:
BayesOpt 2017
NIPS Workshop on Bayesian Optimization
December 9, 2017
Long Beach, USA

bellingcat!

We introduced ROBO, a flexible Bayesian optimization framework in python. For standard GP-based
blackbox optimization, its performance is on par with Spearmint while using the permissive BSD
license. Most importantly, to the best of our knowledge, ROBO is the first BO package that includes
Bayesian neural network models and that implements specialized BO methods that go beyond the
blackbox paradigm to allow orders of magnitude speedup.

volumes
1) vectors and matrices
2) derivatives
3) integrals

“The potential amount of debt is an iceberg with titanic credit risks,” S&P credit analysts led by Gloria Lu wrote in a report Tuesday.

With the national economy slowing, and a Beijing-set quota for issuance of local-government bonds not being enough to fund infrastructure projects to support regional growth, authorities across the country have resorted to LGFVs to raise financing (Local Government Financing Vehicles)

Because foreign-law bonds are often priced in a foreign currency, we need to adjust the observed yields for the currency premium

Snoek 2012 paper
code here: http://www.cs.toronto.edu/˜jasper/software.html
TPA: https://github.com/jaberg/hyperopt/wiki

DeepMind's paper on bayesian optimization

overview of bayesian optimization by the author of Spearmint

analysis suggests that the Earth System may be approaching a planetary threshold that could lock in a continuing rapid pathway toward much hotter conditions—Hothouse Earth. This pathway would be propelled by strong, intrinsic, biogeophysical feedbacks difficult to influence by human actions, a pathway that could not be reversed, steered, or substantially slowed.

Where such a threshold might be is uncertain, but it could be only decades ahead at a temperature rise of ∼2.0 °C above preindustrial, and thus, it could be within the range of the Paris Accord temperature targets.

The impacts of a Hothouse Earth pathway on human societies would likely be massive, sometimes abrupt, and undoubtedly disruptive.

2 °C warming would translate to 1,119 (748–1,392) or 1,327 (1,123–1,516) cities committed under the baseline or triggered assumptions, respectively, and would affect land that is home to 19.0 (11.6–25.0) or 23.0 (16.8–28.1) million people today, respectively. Warming of 4 °C would increase central estimates to more than 1,745 cities and 30 million people under either assumption.