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updated docs
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<pre>
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Minimize: f(w) == 0.5*dot(w,w) + C*R(w)
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Where R(w) is a convex function and C > 0
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Where R(w) is a user-supplied convex function and C > 0
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</pre>
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<br/>
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<br/>
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@ -12,13 +12,38 @@
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<current>
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New Stuff:
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- Added the solve_qp_using_smo() function to solve certain quadratic
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programs.
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- Added the oca object. It is an implementation of the Optimized Cutting
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Plane Algorithm.
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- Added a linear SVM trainer that uses oca.
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- Added an implementation of the Histogram of Oriented Gradients algorithm
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- Added a simple tool for making image pyramids
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- Added the running_covariance object
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- Added a simple linear (i.e. non-kernelized) kmeans implementation
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- Added support for serializing dlib::int64
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Non-Backwards Compatible Changes:
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- Changed the definition of dlib's sparse vector format to require
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unsigned integral keys. Having this requirement is nice because it
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creates a simple correspondence between dense vector index values and
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sparse vector keys. The previous sparse vector definition was
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excessively generic.
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- Renamed sparse_vector::dot_product() to sparse_vector::dot() so that
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both dense and sparse vectors have a global function with the same
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name (i.e. dot()).
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Bug fixes:
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- Fixed a bug discovered by Mitchell Peabody. In some instances trying to
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deserialize a std::vector would fail to compile.
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Other:
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- Increased the number of template arguments of the type_safe_union from 10
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to 20. Additionally, I made the get_id() function public and renamed it
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to get_type_id(). I also added a comment explaining the serialization
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format of type_safe_union objects.
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- Moved the optimization algorithms into their own page in the documentation.
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- Added a Suggested Books page to the documentation
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</current>
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