Ready for alpha2 release.

- complete documentation
- add TODO
- update copyright years

TODO

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+Things that need to be done for 2.0:
+
+The Core modules is essentially ready. Now we need more modules:
+- QR decomposition
+  -> ANY VOLUNTEER? I can provide a scanned copy of Golub&vanLoan.
+  -> investigate various algorithms, balance numerical stability vs. speed,
+     maybe go for a different algos for fixed-size (small) vs. dynamic-size
+     (typically bigger).
+  -> applications: eigenvalues, eigenspaces, operator norm...
+  -> more applications: by computing eigenvalues of a companion matrix,
+     we can provide a general polynomial solver. I can explain that to
+     a potential volunteer... also this is optional.
+
+- SVD decomposition
+  -> ANY VOLUNTEER?
+  -> Same remarks as for QR.
+  -> applications include pseudo-inverse and linear regression (in Eigen1 we
+     did linear regression with LU but that was not very good).
+
+- Array
+  -> ANY VOLUNTEER?
+  -> We should group in this module all the functionality that consists in
+     abusing a matrix as an array. Many people have asked for such
+     functionality:
+  -> coefficient-wise product (a.k.a. "Schur product" of matrices).
+     This should return a new expression. Look at Core/Sum.h for a starting
+     point.
+  -> Apply some function (such as "exp") to every coefficient of a matrix.
+     This should return a new expression. Look at Core/Conjugate.h for a
+     starting point.
+  -> stack matrices horizontally and vertically to form larger matrix
+     expressions. Look at Core/Block.h, Core/Minor.h for a starting point.
+  -> sum over the elements of a vector (look at Core/Trace.h to get
+     a starting point).
+  -> Given a matrix, return a vector whose i-th coefficient is the sum
+     of the coefficients in the i-th column of that matrix. Same for rows.
+     -> This should return an actual vector (i.e. evaluate immediately),
+        not an expression, because a loop is involved.
+     -> Yes, this can be done as "matrix * VectorType::ones()" but we
+        should implement it separately so as to not be too hard on the
+        compiler.
+
+- Gaussian elimination
+  -> LEAVE IT TO ME as I did something similar in Eigen1.
+  -> I don't call this module LU because I want to code certain operations
+     such as inverse in an optimized way that bypasses the LU decomposition.
+     But yes, LU is one of the things that will be provided by this module.
+  -> Other things to do here: determinant, basis of kernel, basis of range,
+     antecedent etc...
+  -> Should be do a "simple linear solver" like in eigen1? Did anybody
+     use it?
+  -> linear regression should use SVD instead. However as a temporary
+     solution we could borrow the implementation from eigen1, using gaussian
+     elimination.
+
+- Geometry
+  -> LEAVE IT TO ME as I did something similar in Eigen1.
+  ->low-dimensional geometry (quaternions, cross product, rotations)
+  ->projective geometry(opengl matrices, Qt matrices)
+  ->euclidean geometry (Gram-Schmidt)
+  
+- Sparse objects support, by wrapping GMM++
+  -> ANY VOLUNTEER? I'm looking at the folks already used to GMM++. I will
+     provide support but am not used to GMM++ so wouldn't like to have to do
+     all that alone.
+  -> Goal: provide a nice wrapper around GMM++ with Qt-style copy-on-write
+     (I can code the copy-on-write part if you don't want to do it)
+  -> Very important for Krita 2.1 and Step
+  -> No expression templates here. So the API won't be quite identical to the
+     rest of Eigen. Should be release under a different name? "Speisen" comes
+     to mind ;)
+  -> No need to wrap all of GMM++. Only sparse objects. Only what's useful
+     for KOffice 2.1 and Step (if you want more, do it).
+  -> Step uses:
+     -gmm::cg, constrained_cg
+     -dantzig algorithm
+     -types: gmm::row_matrix, col_matrix, rsvector, array1D_reference
+  -> What is needed for Krita?