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diff --git a/README.md b/README.md
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+++ b/README.md
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-GenSVM C Package				{#mainpage}
+GenSVM C Package
 ================
 
 GenSVM: A Generalized Multiclass Support Vector Machine.
 
 Author: Gertjan van den Burg (<gertjanvandenburg@gmail.com>)
 
-Version: 0.1
-
 Introduction
 ------------
 
-This is the introduction
+This is the C library for the GenSVM method. GenSVM is a general multiclass 
+support vector machine, which you can use for classification problems with 
+multiple classes. Training GenSVM in cross-validation or grid search setups 
+can be done efficiently due to the ability to use warm starts. See the 
+[paper]() for more information, and Usage below for how to use GenSVM.
+
+The library has support for datasets in [MSVMpack]() and [LibSVM/SVMlight]() 
+format, and can take advantage of sparse datasets. There is also (preliminary) 
+support for nonlinear GenSVM through kernels.
+
+For documentation on how the library is implemented, see the Doxygen 
+documentation available [here](). There are also many unit tests, which you 
+can use to further understand how the library works. Test coverage for the 
+current version is reported [here]().
 
 Usage
 -----
 
-Describe the usage of the program here
+First, download and compile the library. Minimal requirements for compilation 
+are a working BLAS and LAPACK installation, which you can likely obtain from 
+your package manager. It is however recommended to use ATLAS versions of these 
+libraries, since this will give a significant increase in speed. If you choose 
+not to use ATLAS, remove linking with ``-latlas`` in the ``LDFLAGS`` variable 
+in the Makefile.
 
-License
--------
+Then, compile the library with a simple:
+
+    make
+
+If you like to run the tests, use ``make test`` on the command line. 
+
+After successful compilation, you will have two executables ``gensvm`` and 
+``gensvm_grid``. Type:
+
+    ./gensvm
+
+To get an overview of the command line options to the executable (similar for 
+``gensvm_grid``).
+
+The ``gensvm`` executable can be used to train a GenSVM model on a dataset 
+with a single hyperparameter configuration, whereas the ``gensvm_grid`` 
+executable can be used to run a grid search on a dataset.
+
+Here's an example of using the ``gensvm`` executable on a single dataset, with 
+some custom parameters:
+
+    ./gensvm -l 1e-5 -k 1.0 -p 1.5 data/iris.train
+
+This fits the model with regularization parameter ``1e-5``, Huber hinge 
+parameter ``1.0`` and lp norm parameter ``1.5``, and default settings 
+otherwise. On my computer this yields a model with 18 support vectors in about 
+0.1 seconds. The ``gensvm`` executable can also be used to get predictions for 
+a test dataset, if it is supplied as final argument to the command. In this 
+case, predictions will be printed to stdout, unless an output file is 
+specified with the ``-o`` option.
+
+The ``gensvm_grid`` executable can be used to run a grid search on a dataset.
+The input to this executable is a file (called a grid file), which specifies 
+the values of the parameters. See the ``training`` directory for examples and 
+the documentation [here]() for more info on the file format. One important 
+thing to note is that when the ``repeats`` field has a positive value, a 
+so-called "consistency check" will be performed after the grid search has 
+finished. This is a robustness check on the best performing configurations, to 
+find the best overall hyperparameter configuration with the best performance 
+and smallest training time. In this robustness check warm-starts are not used, 
+to ensure the observations are independent measurements of training time.
 
-Put some license information here
+Here's an example of running ``gensvm_grid`` without repeats on the iris 
+dataset:
+
+    ./gensvm_grid training/iris_norepeats.training
+
+On my computer this runs in about 8 seconds with 342 hyperparameter 
+configurations. Alternatively, if consistency checks are desired we can run:
+
+    ./gensvm_grid training/iris.training
+
+which runs the same grid search but also does 5 consistency repeats for each 
+of the configurations with the 5% best performance. Note that the performance 
+is measured by cross-validated accuracy scores. This example runs in about 13 
+seconds on my computer.
 
 Reference
 ---------
-Reference to the published paper, include BibTeX entry as code block here.
+
+If you use GenSVM in any of your projects, please cite the GenSVM paper 
+available at [link](link). You can use the following BibTeX code:
+
+    bibtex here
+
+License
+-------
+
+    Copyright 2016, G.J.J. van den Burg.
+
+    GenSVM is free software: you can redistribute it and/or modify
+    it under the terms of the GNU General Public License as published by
+    the Free Software Foundation, either version 3 of the License, or
+    (at your option) any later version.
+
+    GenSVM is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+    GNU General Public License for more details.
+
+    You should have received a copy of the GNU General Public License
+    along with GenSVM. If not, see <http://www.gnu.org/licenses/>.
+
+    For more information please contact:
+
+    G.J.J. van den Burg
+    email: gertjanvandenburg@gmail.com
diff --git a/doc/Doxyfile b/doc/Doxyfile
index 4731fe8..348f159 100644
--- a/doc/Doxyfile
+++ b/doc/Doxyfile
@@ -934,7 +934,7 @@ FILTER_SOURCE_PATTERNS =
 # (index.html). This can be useful if you have a project on for instance GitHub
 # and want to reuse the introduction page also for the doxygen output.
 
-USE_MDFILE_AS_MAINPAGE =
+USE_MDFILE_AS_MAINPAGE = ./README.md
 
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