mention that exponential cone also works in docs #250
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Do exponential cones work? (I haven't tried.) x-ref #228 (comment), #50 |
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matbesancon
reviewed
May 1, 2023
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| This package has two major backends, available via the `reverse_differentiate!` and `forward_differentiate!` methods, to differentiate models (quadratic or conic) with optimal solutions. | |||
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| !!! note | |||
| Currently supports *linear programs* (LP), *convex quadratic programs* (QP) and *convex conic programs* (SDP, SOCP constraints only). | |||
| Currently supports *linear programs* (LP), *convex quadratic programs* (QP) and *convex conic programs* (SDP, SOCP, exponential cone constraints only). | |||
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| Currently supports *linear programs* (LP), *convex quadratic programs* (QP) and *convex conic programs* (SDP, SOCP, exponential cone constraints only). | |
| Currently supports convex quadratic conic programs (convex quadratic objective, conic constraints). The cone needs to have `MathOptSetDistances.projection_gradient_on_set` and `MathOptSetDistances.projection_on_set` implemented. |
Even broader
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@currymj thanks for the PR! |
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While most of the docs just refer to "conic programs", the note at the front specifically says only second-order and semidefinite programming is supported. this adds a small mention that the exponential cone is also supported.