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Always interested in offers/projects/new ideas. Eclectic experience in fields like: numerical computing; Python web; Java enterprise; functional languages; GPGPU; SQL databases; etc. Based in Santiago, Chile; telecommute worldwide. CV; email.

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Expert Data Reduction

From: "andrew cooke" <andrew@...>

Date: Sun, 11 Nov 2007 21:50:47 -0300 (CLST)

For some time I have been thinking about a data reduction system that
supports both distributed computing and lazy evaluation.  The basic idea
is that you define a final image in terms of a graph of intermediate
images (nodes) and processes (edges).  Requesting an image triggers the
generation of input images (and so on).  One advantage of this approach is
that "what-if" exploration is simplified.  Another advantage is that it
may lead to pipelines "for free" (by generalising the graph).

I just stumbled across Pyke - http://pyke.sourceforge.net/ - an inference
system written in Python which can associate functions with backwards
chaining rules to generate code.

A quick sidetrack on logic programming:  expert systems and the like can
work in two ways, either starting with basic facts and finding rules that
lead to the expected result, or starting with the result and finding rules
that lead back to the initial conditions.

This seems to connect with the data reduction idea.  You can imagine a
system which has a set of rules about how to reduce data, and which is
given a set of input data and a target: produce a final image.  The system
would infer the correct process and can then construct the graph and
generate python code (the pipeline).

It's not a silver bullet.  Nothing addresses caching, for example, but it
seems like a step in the right direction.


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