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

Sun May 29 17:05:17 UTC 2011

Here's a class of problems I'm interested in.

Given a function f:a->b, and a known y in b, find an x in a such that
f(x)~=y.

This problem is only solvable if f has certain characteristics, but it has
many very exciting applications. We can search for the muscle movements
underlying a speech act, the fingerings behind a piece of music, and the
texture on the set of an old tv show.

Calling this machine learning is a bit of a stretch, but sure, we can talk
about it. Just don't expect to much rigor from me yet.

On Sat, May 28, 2011 at 7:32 PM, Brian Morris <cymraegish at gmail.com> wrote:

> I apologize that perhaps I was all over the place before in this thread. As
> far as the algorithms and projects go I am very interested in anything with
> longer term really research stuff especially if it might lead to
> publication. I'll try my best to get to ML meeting this week if I can.
>
> My interest in ML did indeed evolve from Linuistics/CogSci/Philosopy;
> however my formal training was in Math/NumericalScientificComputing. Just I
> got away from the latter for some years and coming back in reading a lot got
> into the former by self-study. Gradually got more into Computational
> linguistics and then out again and exploring some real world problems
> interest in the ML group. My more recent math interests mostly in Logic/
> reasoning models.
>
> The wiki page for ML at Noisebridge lists a ML video course from Stanford (
> see https://www.noisebridge.net/wiki/NBML_Course) , but last week I was
> indeed looking at ESL text which Mike included in his refs for random
> forests (the first presentation he gave before last week).
>
> My web scraping by hand led me to two or three groups, in the east and
> midwest, some connections way back MIT and Yale but more recently Mich,
> Indiana and CMU (Europy: a) maybe some Edinburgh school as well ? Used the
> term ML back in the late 60's to distinguish them from AI workers b) Luc
> Steels' work on evolution of language with Alife and Robotics). Most
> striking to me this particular HRI group
>
> http://hrilab.cs.tufts.edu/research/
>
>
>  and especially impressed by perspective of the CMU Machine Learning dept
> leader Tom Mitchell:
>
> Book:
> www.cs.cmu.edu/~*tom*/mlbook.html
> Interview on his perspective:
> videolectures.net/mlas06_*mitchell*_itm/
>
>
>
>
>
>
>
> On Sat, May 28, 2011 at 4:56 PM, Kai Chang <kai.salmon.chang at gmail.com>wrote:
>
>> I did cognitive science at UVA, and there the approach was quite
>> different. The curriculum seemed heavily influenced by MIT, with more focus
>> on linguistics, pyschology and philosophy. Not sure what the approach at CMU
>> is like.
>>
>> At Stanford, the emphasis seems to be on optimization, classification,
>> etc. The problem requires a fitness function or other well-defined metrics
>> to test against. More related to math and statistics than cognition in
>> general.
>>
>> For broader questions of cognition and learning, there are several other
>> traditions. Logicians and linguists: Wittgenstein, Godel and Saussure.
>> Phenomenologists: Heidegger, Merleau-Ponty, Marx. Philosophers: Hume,
>> Nietzsche, Deleuze. Buddhism also has very nuanced views on the subject.
>>
>> These traditions share doubts about symbolic formalism and rationality as
>> sufficient means of describing human intelligence and experience.
>>
>> For example, we have overwhelming evidence that neurons serve as building
>> blocks in networks with the capability to learn broad classes of problems.
>> But we still have no foundation to demonstrate that neurons produce our
>> phenomenal experience (the rich, inner, subjective world).
>>
>> Anyways. Crutcher, I'll drop by next week. I got really busy last time ML
>> was doing a group project. I'd be interested in hearing about these other
>> applications of metaheuristic search too!
>>
>> On Fri, May 27, 2011 at 8:14 PM, David Faden <dfaden at gmail.com> wrote:
>>
>>> 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
>>>>>
>>>>>
>>>>
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>>>>
>>>>
>>>
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>>>
>>>
>>
>

-- 
Crutcher Dunnavant <crutcher at gmail.com>
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