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<meta name="Author" content="Ronan Collobert">
<meta name="Description" content="Torch Library.">
<meta name="Keywords" content="Machine Learning.">
<title>Torch Library</title>
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<center><img SRC="images/title.jpeg" ALT="[Torch]" NOSAVE height=137 width=220><img SRC="images/release.jpeg" NOSAVE height=18 width=77>
<p><img SRC="images/torche_wind.jpeg" ALT="[XXXXX]" NOSAVE height=32 width=32></center>
<div align=right><i><font size=-1><a href="http://www.idiap.ch/~collober">Ronan
Collobert</a>,
<a href="mailto:collober@iro.umontreal.ca">collober@iro.umontreal.ca</a></font></i></div>
<center><table COLS=5 WIDTH="100%" BGCOLOR="#FFCC00" NOSAVE >
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<td NOWRAP NOSAVE><a href="about.html"><img SRC="images/about_bx.jpeg" ALT="[About]" NOSAVE BORDER=0 height=32 width=60></a></td>
<td NOWRAP NOSAVE><a href="introduction.html"><img SRC="images/introduction_b.jpeg" ALT="[Introduction]" NOSAVE BORDER=0 height=32 width=95></a></td>
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<p><img SRC="images/curriculum.jpeg" ALT="[Curriculum Vitae]" NOSAVE height=41 width=253>
<blockquote>Currently, <b><i>Torch</i></b> is developed at <a href="http://www.idiap.ch">IDIAP</a>,
in Switzerland and at <a href="http://www.iro.umontreal.ca">Universite
de Montreal</a> in Québec.
<br>
<br>
<table COLS=2 WIDTH="100%" NOSAVE >
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<center>The <b><i>Torch</i></b> Team
<br><img SRC="images/team.jpeg" NOSAVE height=100 width=270></center>
</td>
<td>
<center><b><font size=-1>(Author)</font></b>
<br><i><a href="http://www.idiap.ch/~collober">Ronan Collobert</a>, <a href="mailto:collober@iro.umontreal.ca">collober@iro.umontreal.ca</a></i>
<p><b><font size=-1>(Main Contributors)</font></b>
<br><i><a href="http://www.idiap.ch/~bengio">Samy Bengio</a>, <a href="mailto:bengio@idiap.ch">bengio@idiap.ch</a></i>
<br><i><a href="http://www.idiap.ch/~marietho">Johnny Mariethoz</a>, <a href="marietho@idiap.ch">marietho@idiap.ch</a></i></center>
</td>
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</blockquote>
<p><br><img SRC="images/what.jpeg" ALT="[What's that ?]" NOSAVE height=38 width=208>
<blockquote>It's a machine-learning library, written in C++.
<br>It's distributed under the <a href="http://www.gnu.org/licenses/gpl.html">GPL</a>
licence.
<p>It is, and it will be in development forever.
<br>It's for Unix and Linux systems: other systems aren't supported at
all.
<br>It has been successfully compiled on Linux, SunOS, FreeBSD and OSF1.
<p>Currently, the main features are the following:
<ul>
<li>
A lot of things in <i>gradient-machines</i>, that is, machines which could
be learned with gradient descent. This includes Multi-Layered Perceptrons,
Radial Basis Functions and Mixtures of Experts. In fact there are a lot
of small "modules" available (Linear module, Tanh module, SoftMax module...)
that you can plug as you want to get what you want.</li>
<li>
<i>Support Vector Machine</i>, in classification and regression.</li>
<li>
A <i>Distribution</i> package which includes <i>Kmeans</i>, <i>Gaussian
Mixture Models, Hidden Markov Models </i>and<i> Bayes Classifier. </i>Moreover
classes for <i>speech recognition with embedded training </i>are available
is this package.</li>
<li>
Ensemble models such as Bagging and Adaboost.</li>
<li>
A few non-parametric models such as K-nearest-neighbors, Parzen Regression
and Parzen Density Estimator.</li>
</ul>
As it's an open library, we encourage everybody to develop new packages
which could then be included in future versions on the official website
(as long as it follows the <a href="codings.html">coding guidelines</a>).</blockquote>
<img SRC="images/why.jpeg" ALT="[Why should I use that ?]" NOSAVE height=47 width=350>
<blockquote>The aim of <b><i>Torch </i></b>is to provide the state-of-the-art
of the best algorithms in machine learning. Therefore...
<ul>
<li>
If you know C++,</li>
<br>
<li>
If you're working in machine learning and want to develop your own algorithms,</li>
<li>
or if you want to use well-known machine-learning algorithms</li>
</ul>
... <b><i>Torch </i></b>is made for you!</blockquote>
<div align=right>
<hr WIDTH="100%"><b><i><font size=-1>Thanks to IDIAP, and especially to
Frank Formaz for the URL of the website...</font></i></b></div>
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