Machine Learning Meetup Notes: 2008-12-17: Difference between revisions
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(New page: These are the mostly-raw notes from the machine learning group meeting on 2008-12-17. People attending: Bill, Jean, Jeremy, Josh, Matt, Mike, Praveen (and ruben made a cameo) Here's what...) |
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'''matt''' | '''matt''' | ||
* interested in swarms and modeling multiple agents as applied to robots | * interested in swarms and modeling multiple agents as applied to robots | ||
* [http://www.amazon.com/Intelligence-Jeff-Hawkins/dp/0805074562 | * [http://www.amazon.com/Intelligence-Jeff-Hawkins/dp/0805074562 Jeff Hawkins, On Intelligence (at Amazon)] | ||
* [http://www.onintelligence.org/ | * [http://www.onintelligence.org/ On Intelligence, the website] | ||
'''bill''' | '''bill''' | ||
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* fun problem is document clustering, semantic relatedness in documents | * fun problem is document clustering, semantic relatedness in documents | ||
* interested in unsupervised and semisupervised learning | * interested in unsupervised and semisupervised learning | ||
* [http://glaros.dtc.umn.edu/gkhome/views/cluto/ | * [http://glaros.dtc.umn.edu/gkhome/views/cluto/ Cluto, a set of clustering tools with great visualization] | ||
* boosting was mentioned | * boosting was mentioned | ||
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* interested in creating a taxonomy/survey of machine learning techniques | * interested in creating a taxonomy/survey of machine learning techniques | ||
* genetic neural networks google talk | * genetic neural networks google talk | ||
* [http://www.cs.waikato.ac.nz/ml/weka/ | * [http://www.cs.waikato.ac.nz/ml/weka/ Weka homepage], a machine learning toolkit | ||
* [http://www.youtube.com/watch?v=_m97_kL4ox0 | * [http://www.youtube.com/watch?v=_m97_kL4ox0 Polyworld: Using Evolution to Design Artificial Intelligence], a google techtalk about evolving neural network topologies via genetic algorithms | ||
* [http://www.youtube.com/watch?v=AyzOUbkUf3M | * [http://www.youtube.com/watch?v=AyzOUbkUf3M The Next Generation of Neural Networks], a google techtalk on Restricted Boltzmann Machines, used for the NIST digit recognition task. | ||
* [http://kittenwars.com | * [http://kittenwars.com An example of human-driven binary comparison of attributes] | ||
'''jean''' | '''jean''' | ||
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* interested in exploring/surveying different techniques (taxonomy) | * interested in exploring/surveying different techniques (taxonomy) | ||
* in particular with applications in eeg/fmri us | * in particular with applications in eeg/fmri us | ||
* [http://www.pymvpa.org/ | * [http://www.pymvpa.org/ Python MultiVariate Pattern Analysis], a python packages that implements a lot of Multivariate pattern analysis algorithms | ||
* [http://www.gnu.org/software/octave/ | * [http://www.gnu.org/software/octave/ GNU Octave], the GNU implementation of matlab (good matlab replacement for PCA) | ||
'''praveen''' | '''praveen''' | ||
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* looking to collaborate on anything, wanting to get more hands on PCA experience | * looking to collaborate on anything, wanting to get more hands on PCA experience | ||
* perl script that will make million$ | * perl script that will make million$ | ||
* [http://www.swarm.org/ | * [http://www.swarm.org/ Swarm Development Group Wiki], | ||
* [http://en.wikipedia.org/wiki/Self-organizing_map | * [http://en.wikipedia.org/wiki/Self-organizing_map Self-organizing maps], a neural network technique he's worked with in the past | ||
* [http://www.pbs.org/wgbh/nova/apegenius/program.html | * [http://www.pbs.org/wgbh/nova/apegenius/program.html Ape Genius (NOVA)], source of some anecdotes we shared (chapter 6) | ||
'''ruben110''' | '''ruben110''' |
Latest revision as of 15:33, 26 December 2008
These are the mostly-raw notes from the machine learning group meeting on 2008-12-17.
People attending: Bill, Jean, Jeremy, Josh, Matt, Mike, Praveen (and ruben made a cameo)
Here's what the people who attended were interested in:
matt
- interested in swarms and modeling multiple agents as applied to robots
- Jeff Hawkins, On Intelligence (at Amazon)
- On Intelligence, the website
bill
- in the past work on optimization of functions (optimization theory), interested in just learning anything
mike
- interested in learning and absorbing new info
jeremy
- works at SRI, visting fellow in speech recognition and machine translation
- fun problem is document clustering, semantic relatedness in documents
- interested in unsupervised and semisupervised learning
- Cluto, a set of clustering tools with great visualization
- boosting was mentioned
josh
- works for mechanical zoo
- looking to collaborate with other people
- interested in creating a taxonomy/survey of machine learning techniques
- genetic neural networks google talk
- Weka homepage, a machine learning toolkit
- Polyworld: Using Evolution to Design Artificial Intelligence, a google techtalk about evolving neural network topologies via genetic algorithms
- The Next Generation of Neural Networks, a google techtalk on Restricted Boltzmann Machines, used for the NIST digit recognition task.
- An example of human-driven binary comparison of attributes
jean
- working at ucsf doing cognitive research
- interested in exploring/surveying different techniques (taxonomy)
- in particular with applications in eeg/fmri us
- Python MultiVariate Pattern Analysis, a python packages that implements a lot of Multivariate pattern analysis algorithms
- GNU Octave, the GNU implementation of matlab (good matlab replacement for PCA)
praveen
- currently @ linden lab
- worked with gene expresssion data mining, music preference and basket analysis,
- looking to collaborate on anything, wanting to get more hands on PCA experience
- perl script that will make million$
- Swarm Development Group Wiki,
- Self-organizing maps, a neural network technique he's worked with in the past
- Ape Genius (NOVA), source of some anecdotes we shared (chapter 6)
ruben110
- facial recognition anecdotes
Collaborative project kick off for year end 2008[edit]
- Create a survey/taxonomy list of ML techniques -- when setting out to do a particular machine learning task, what is the shortlist of techniques/tools/insights?