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Updates in this release:
- ``MVMDS`` can now also accept distance matrices as input, rather than only views of data with samples and features
- A new clustering algorithm, ``CoRegMultiviewSpectralClustering`` - co-regularized multi-view spectral clustering functionality
- Some attribute names slightly changed for more intuitive use in ``DCCA``, ``KCCA``, ``MVMDS``, ``CTClassifier``
- Option to use an Incomplete Cholesky Decomposition method for ``KCCA`` to reduce up computation times
- A new module, ``factorization``, containing the ``AJIVE`` algorithm - angle-based joint and individual variance explained
- Fixed issue where signal dimensions of noise were dependent in the GaussianMixtures class
- Added a dependecy to ``joblib`` to enable parallel clustering implementation
- Removed the requirements for ``torchvision`` and ``pillow``, since they are only used in tutorials