A quick last-minute reminder of a few streams/sessions at IFORS
http://ifors2017.ca/ that could be of interest to anyone interested in
the overlap and intersections of statistics/machine learning (within
data science) and optimisation and metaheuristics.
Note, the conference talks place in Quebec City in Canada during July
17-21, 2017.
In particular, abstracts are welcome for work that either
- uses machine learning / statistics to improve optimisation techniques
using a variety of ideas that can appear under many different names
including adaptive or reactive search, hyper-heuristics, data analytics
for search, etc.
or
- uses advanced optimisation/search techniques such as mathematical
programming or heuristics/metaheuristics in order to increase the
performance of methods to solve machine-learning or statistics problems.
Note that the abstract submission process is very lightweight just
requiring a short abstract, not an extended abstract.
Please consider to submit an abstract to one of the following streams,
using the IFORS submission site: http://ifors2017.ca/submit-abstract
Stream: Data Science meets Optimisation Data Science meets Optimisation
At the IFORS website use the code 7eb193df
Stream: Hyperheuristics (which is intended to include any
general-method method to accelerate metaheuristics and not only the
specific meaning of hyperheuristics).
At the IFORS website use the code d47b063f
regards
Andrew
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