[Noisebridge-discuss] [ml] I am interested in starting an optimization group at noisebridge (BetterBridge? TrollSearch?)

[David Faden]

West = http://www-stat.stanford.edu/~tibs/ElemStatLearn/ ?

What's the East Coast book?

How would you classify http://aima.cs.berkeley.edu/ ?

Interesting to hear about this division. Thanks.

On Fri, May 27, 2011 at 7:03 PM, Brian Morris <cymraegish at gmail.com> wrote:

> I am very much wanting the more doing / project as-a-group thing.
>
> I probably won't make it to the ML meeting this coming week tho (most 3/4
> weeks I am there)
>
> There are two perspectives of what Machine Learning is, might call for lack
> of better terms the Stanford perspective and the Carnegie-Mellon perspective
> (from the location of the authors of two popular texts), or East and West if
> you like.
>
> I generally take the East side and Mike the west,  but also would like to
> work on more general problems with a group, maybe  less Statistical Learning
> ... and / or problems which have orderings rather than actual or precise
> numerical values (ordinal variables), so that optimization is possible even
> if formulas cannot be given or numerical data is either too imprecise or
> simply unavailable. [Like if you have labels like letter grades, but not
> numerically based, how best to assign / design content ?]
>
> Maybe applies to some problems in knowledge management, natural language /
> linguistics problems, policy decision making (how to maximize job
> satisfaction for instance), intelligence analysis.
>
> Kinda short on specific problems, might have to Troll Search them.
>
> By the way, what's the best way to produce a table of contents rather than
> an index (given say a bunch of text scraped off the Web) ?
>
> On Fri, May 27, 2011 at 1:27 PM, Crutcher Dunnavant <crutcher at gmail.com>wrote:
>
>> The ML group seems to have grown up quite a bit since the last time I paid
>> attention; and I think I should start participating; as the page lists many
>> things I'd like to learn and play with.
>>
>> I am specifically suggesting a group-project oriented group; rather than a
>> research group or class. Something that would yield finished projects;
>> something where we collaborate on a common code base and problem set, beat
>> it to death, publish it (5mof?); and move on to the next one.
>>
>> There are many applications of metaheuristic search outside machine
>> learning; and I don't want to hijack a group which looks healthy.
>>
>> On Fri, May 27, 2011 at 12:00 PM, Mike Schachter <mike at mindmech.com>wrote:
>>
>>> Hi Crutcher,
>>>
>>> I'd be interested in black box optimization. The machine learning
>>> group meets up on Wednesdays at 7:30pm in the Church classroom:
>>>
>>> https://www.noisebridge.net/index.php?title=Machine_Learning
>>>
>>> Just speaking for myself, I'd be happy to see you share time/space
>>> with the ML group to talk about optimization, as it's a core part of
>>> machine learning.
>>>
>>> We don't have anything going on next week, and you're welcome to
>>> come in to talk about stuff, I'd be happy to discuss optimization with
>>> you!
>>>
>>>  mike
>>>
>>>
>>>
>>> On Fri, May 27, 2011 at 10:10 AM, Crutcher Dunnavant <crutcher at gmail.com>
>>> wrote:
>>> > I am very interested in starting a black box optimization search group
>>> at
>>> > noisebridge. This field is called "metaheauristics"; but the name is a
>>> > stupid historical artifact (so says everyone in the field).
>>> > Optimization is, given a function f(x), searching for the x which
>>> yields the
>>> > best f(x). Black box optimization is a sub-field of optimization where
>>> you
>>> > can't analyize the function f to determine what values of x are likely
>>> to be
>>> > good; so you have to search the space for them.
>>> > The following algorithms are ALL metaheuristic optimization:
>>> > Hill Climbing (aka. Gradient Assent/Descent)
>>> > Genetic Search
>>> > Genetic Programming
>>> > Ant Colony Systems
>>> > Particle Swarm Optimization
>>> > I've recently read a fabulous undergraduate text on the subject, very
>>> > approachable, called "Essentials of Metaheuristics".
>>> > The book in question is available from Lulu and Amazaon:
>>> > http://www.cs.gmu.edu/~sean/book/metaheuristics/
>>> > or you can just download the PDF.
>>> > http://www.cs.gmu.edu/~sean/book/metaheuristics/Essentials.pdf
>>> >
>>> > If you aren't sure what I'm talking about, read the first chapter or
>>> two. If
>>> > you have a background in programming, you should be able to follow it
>>> > trivially.
>>> > What I want TrollSearch to do: Build Shit
>>> > Let's find interesting problems; and build search algorithms over them.
>>> This
>>> > can apply to evolving good fit 3d models for the printer; making
>>> techno; or
>>> > identifying penii.
>>> > I'd like TrollSearch to look much more like SpaceBridge than like the
>>> Python
>>> > Class.
>>> > Please comment in-thread if you are interested.
>>> > --
>>> > Crutcher Dunnavant <crutcher at gmail.com>
>>> >
>>> > _______________________________________________
>>> > Noisebridge-discuss mailing list
>>> > Noisebridge-discuss at lists.noisebridge.net
>>> > https://www.noisebridge.net/mailman/listinfo/noisebridge-discuss
>>> >
>>> >
>>>
>>
>>
>>
>> --
>> Crutcher Dunnavant <crutcher at gmail.com>
>>
>> _______________________________________________
>> Noisebridge-discuss mailing list
>> Noisebridge-discuss at lists.noisebridge.net
>> https://www.noisebridge.net/mailman/listinfo/noisebridge-discuss
>>
>>
>
> _______________________________________________
> ml mailing list
> ml at lists.noisebridge.net
> https://www.noisebridge.net/mailman/listinfo/ml
>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.noisebridge.net/pipermail/noisebridge-discuss/attachments/20110527/333591a4/attachment-0003.html>