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Mon, 09. Apr 12
JMLC journal publication accepted
My paper "Minimizing Data Consumption with Sequential Online Feature Selection" has finally been accepted at the Journal of Machine Learning and Cybernetics and is now in print. A pre-print version can be downloaded from the publications page.
Wed, 04. Jan 12
PyBrain 0.3.1 released
While we're still aiming for a bigger update for the 0.4 release, we
decided to put out a minor release (0.3.1) that captures all the
recent changes.

Here's some of the changes since the 0.3 release:

- improved black-box optimization framework with new algorithms (xNES, SNES, ...), new benchmarks (Lennard-Jones, noisy functions, ...)

- expanded reinforcement learning framework with e.g. value-based RL algorithms that work with function approximation (Q-lambda, Sarsa-lambda, GQ-lambda, LSTD, ...) and new/updated examples

- sub-sampling connections
- reorganized test scripts
- minor speed improvements

and of course: a large number of bug fixes.

Tue, 22. Nov 11
AI2011 paper selected for special issue publication
My accepted paper at AI 2011 was selected to be published in a special issue of the International Journal of Machine Learning and Cybernetics (IJMLC) for an early 2012 appearance. The publication is separate from and in addition to the AI2011 conference proceedings.
Tue, 16. Aug 11
Paper accepted to AI2011
My paper "Sequential Feature Selection for Classification" has been accepted at the Australasian conference on Artificial Intelligence AI2011 for oral presentation and full paper in the proceedings. The conference takes place in Perth, Australia from 6-8 Dec. later this year, at the Mercure hotel. Coincidentially, I live next door now ;-)
Mon, 11. Oct 10
Python Experiment Suite Paper Accepted
I successfully submitted a manuscript to The Python Papers Journal which describes the Python Experiment Suite I developed. The paper is published here. It can also be found in my publications section.
Mon, 11. Oct 10
Documentation for Python Experiment Suite
My PyExperimentSuite finally got a proper documentation. You can download it here or from the github repository, where ExperimentSuite is hosted. The Python Experiment Suite is an open source software framework written in Python to execute and organize large scale automated software experiments with many useful features
Tue, 29. Jun 10
PyBrain Video
Here's the PyBrain video presentation from the ICML 2010 workshop on Open Source Machine Learning Software with installation tutorial and some use cases.
Fri, 02. Apr 10
Added BibTeX entries
On my publications list, BibTeX entries for most papers are now also available. Feel free to use them if you want to cite any of my papers.
Fri, 02. Apr 10
New Journal Papers
Three journal papers have recently been accepted and are being published. Check out the publications page for more details.
Wed, 27. Jan 10
Proseminar Game Theory in SS 2010
Next semster, I offer a proseminar about Game Theory. We will cover both the classical game theory topics (zero-sum / non-zero sum games, nash equilibrium, minimax algorithm, ...) and some other, game-related topics (altruism, chess computers, back-gammon playing, reinforcement learning, ...). The seminar is full now, but here is the website with the topics. If you are interested, you're welcome to attend the presentations.
Wed, 18. Nov 09
PyBrain 0.3 released
Today we announced the release of the latest version of our machine learning library in Python. PyBrain 0.3 is available for download on the website or directly on GitHub, where we host the project.
Wed, 11. Nov 09
unsolicited email protection
Similar to the ingenius idea of spamgourmet, I programmed my own UCE (unsolicited commercial email) protection feature. Email addresses can be created on the fly (without setup), using a different keyword in front of the @ for a particular site, followed by a dot and the limit, like facebook.5@... Emails arriving at this address are collected by a catchall mailbox and then forwarded to my real email address, or not, if a certain limit (5 in this example) has been reached for this keyword.
Thu, 02. Jul 09
ExperimentSuite on GitHub
My Python script to run experiments and collect data is now available in my github account. It is very generic and works with configuration files. You can run your experiments, kill them in between and continue where you left off. It is multi-core aware (you need python2.6 for this) and can run combinations of parameter ranges for you. All the results are logged in files and folders, and there is a little API that lets you quickly collect and analyse the data. If you want to check it out, just clone it and play around with it. Here's the link:
Fri, 10. Apr 09
I finished my snippets section, a collection of syntax-highlighted code fragments and tutorials. It contains both permanent ones (that others might be interested in as well) and temporary snippets, which are a good way of quickly exchanging clipboard contents over the web.