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.<br>
<br>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.<br>
<br>The wiki page for ML at Noisebridge lists a ML video course from Stanford ( see <a href="https://www.noisebridge.net/wiki/NBML_Course">https://www.noisebridge.net/wiki/NBML_Course</a>) , 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).<br>
<br>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 <br>
<br><a href="http://hrilab.cs.tufts.edu/research/">http://hrilab.cs.tufts.edu/research/</a><br><br><br> and especially impressed by perspective of the CMU Machine Learning dept leader Tom Mitchell:<br><br>Book:<br><span class="f"><cite><a href="http://www.cs.cmu.edu/~">www.cs.cmu.edu/~</a><b>tom</b>/mlbook.html</cite></span><br>
Interview on his perspective:<br><span class="f"><cite></cite></span><span class="f"><cite><a href="http://videolectures.net/mlas06_">videolectures.net/mlas06_</a><b>mitchell</b>_itm/<br><br><br><br><br><br><br><br></cite></span><div class="gmail_quote">
On Sat, May 28, 2011 at 4:56 PM, Kai Chang <span dir="ltr"><<a href="mailto:kai.salmon.chang@gmail.com">kai.salmon.chang@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
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.<div>
<br></div><div>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.</div>
<div><br></div><div>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.</div>
<div><br></div><div>These traditions share doubts about symbolic formalism and rationality as sufficient means of describing human intelligence and experience.</div><div><br></div><div>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).</div>
<div><br></div><div>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!</div>
<div><div></div><div class="h5">
<div><br><div class="gmail_quote">On Fri, May 27, 2011 at 8:14 PM, David Faden <span dir="ltr"><<a href="mailto:dfaden@gmail.com" target="_blank">dfaden@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
West = <a href="http://www-stat.stanford.edu/%7Etibs/ElemStatLearn/" target="_blank">http://www-stat.stanford.edu/~tibs/ElemStatLearn/</a> ?<div><br></div><div>What's the East Coast book?<br><br></div><div>How would you classify <a href="http://aima.cs.berkeley.edu/" target="_blank">http://aima.cs.berkeley.edu/</a> ?</div>
<div><br></div><div>Interesting to hear about this division. Thanks.</div><div><br><div class="gmail_quote"><div><div></div><div>On Fri, May 27, 2011 at 7:03 PM, Brian Morris <span dir="ltr"><<a href="mailto:cymraegish@gmail.com" target="_blank">cymraegish@gmail.com</a>></span> wrote:<br>
</div></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div><div></div><div>I am very much wanting the more doing / project as-a-group thing. <br><br>
I probably won't make it to the ML meeting this coming week tho (most 3/4 weeks I am there)<br>
<br>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.<br>
<br>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 ?]<br>
<br>Maybe applies to some problems in knowledge management, natural language / linguistics problems, policy decision making (how to maximize job satisfaction for instance), intelligence analysis.<br><br>Kinda short on specific problems, might have to Troll Search them. <br>
<br>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) ? <br><div><div></div><div><br><div class="gmail_quote">On Fri, May 27, 2011 at 1:27 PM, Crutcher Dunnavant <span dir="ltr"><<a href="mailto:crutcher@gmail.com" target="_blank">crutcher@gmail.com</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">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.<div>
<br></div><div>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.</div>
<div><br></div><div>There are many applications of metaheuristic search outside machine learning; and I don't want to hijack a group which looks healthy.</div><div><div><div></div><div><br><div class="gmail_quote">
On Fri, May 27, 2011 at 12:00 PM, Mike Schachter <span dir="ltr"><<a href="mailto:mike@mindmech.com" target="_blank">mike@mindmech.com</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Hi Crutcher,<br>
<br>
I'd be interested in black box optimization. The machine learning<br>
group meets up on Wednesdays at 7:30pm in the Church classroom:<br>
<br>
<a href="https://www.noisebridge.net/index.php?title=Machine_Learning" target="_blank">https://www.noisebridge.net/index.php?title=Machine_Learning</a><br>
<br>
Just speaking for myself, I'd be happy to see you share time/space<br>
with the ML group to talk about optimization, as it's a core part of<br>
machine learning.<br>
<br>
We don't have anything going on next week, and you're welcome to<br>
come in to talk about stuff, I'd be happy to discuss optimization with<br>
you!<br>
<br>
mike<br>
<div><div></div><div><br>
<br>
<br>
On Fri, May 27, 2011 at 10:10 AM, Crutcher Dunnavant <<a href="mailto:crutcher@gmail.com" target="_blank">crutcher@gmail.com</a>> wrote:<br>
> I am very interested in starting a black box optimization search group at<br>
> noisebridge. This field is called "metaheauristics"; but the name is a<br>
> stupid historical artifact (so says everyone in the field).<br>
> Optimization is, given a function f(x), searching for the x which yields the<br>
> best f(x). Black box optimization is a sub-field of optimization where you<br>
> can't analyize the function f to determine what values of x are likely to be<br>
> good; so you have to search the space for them.<br>
> The following algorithms are ALL metaheuristic optimization:<br>
> Hill Climbing (aka. Gradient Assent/Descent)<br>
> Genetic Search<br>
> Genetic Programming<br>
> Ant Colony Systems<br>
> Particle Swarm Optimization<br>
> I've recently read a fabulous undergraduate text on the subject, very<br>
> approachable, called "Essentials of Metaheuristics".<br>
> The book in question is available from Lulu and Amazaon:<br>
> <a href="http://www.cs.gmu.edu/%7Esean/book/metaheuristics/" target="_blank">http://www.cs.gmu.edu/~sean/book/metaheuristics/</a><br>
> or you can just download the PDF.<br>
> <a href="http://www.cs.gmu.edu/%7Esean/book/metaheuristics/Essentials.pdf" target="_blank">http://www.cs.gmu.edu/~sean/book/metaheuristics/Essentials.pdf</a><br>
><br>
> If you aren't sure what I'm talking about, read the first chapter or two. If<br>
> you have a background in programming, you should be able to follow it<br>
> trivially.<br>
> What I want TrollSearch to do: Build Shit<br>
> Let's find interesting problems; and build search algorithms over them. This<br>
> can apply to evolving good fit 3d models for the printer; making techno; or<br>
> identifying penii.<br>
> I'd like TrollSearch to look much more like SpaceBridge than like the Python<br>
> Class.<br>
> Please comment in-thread if you are interested.<br>
> --<br>
> Crutcher Dunnavant <<a href="mailto:crutcher@gmail.com" target="_blank">crutcher@gmail.com</a>><br>
><br>
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</blockquote></div><br><br clear="all"><br></div></div>-- <br><div>Crutcher Dunnavant <<a href="mailto:crutcher@gmail.com" target="_blank">crutcher@gmail.com</a>><br>
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