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  2. Matrix regularization - Wikipedia

    en.wikipedia.org/wiki/Matrix_regularization

    The problems can be coupled by adding an additional regularization penalty on the covariance of solutions , ‖ ‖ + ‖ ‖ + ⁡ where models the relationship between tasks. This scheme can be used to both enforce similarity of solutions across tasks, and to learn the specific structure of task similarity by alternating between optimizations ...

  3. Matrix population models - Wikipedia

    en.wikipedia.org/wiki/Matrix_population_models

    The following is an age-based Leslie matrix for this species. Each row in the first and third matrices corresponds to animals within a given age range (0–1 years, 1–2 years and 2–3 years). In a Leslie matrix the top row of the middle matrix consists of age-specific fertilities: F 1, F 2 and F 3. Note, that F 1 = S i ×R i in the matrix

  4. Linear complementarity problem - Wikipedia

    en.wikipedia.org/wiki/Linear_complementarity_problem

    If M is such that LCP(q, M) has a solution for every q, then M is a Q-matrix. If M is such that LCP(q, M) have a unique solution for every q, then M is a P-matrix. Both of these characterizations are sufficient and necessary. [4] The vector w is a slack variable, [5] and so is generally discarded after z is found. As such, the problem can also ...

  5. Branch and bound - Wikipedia

    en.wikipedia.org/wiki/Branch_and_bound

    Branch and bound (BB, B&B, or BnB) is a method for solving optimization problems by breaking them down into smaller sub-problems and using a bounding function to eliminate sub-problems that cannot contain the optimal solution. It is an algorithm design paradigm for discrete and combinatorial optimization problems, as well as mathematical ...

  6. Constraint satisfaction problem - Wikipedia

    en.wikipedia.org/wiki/Constraint_satisfaction...

    Constraint satisfaction problems (CSPs) are mathematical questions defined as a set of objects whose state must satisfy a number of constraints or limitations. CSPs represent the entities in a problem as a homogeneous collection of finite constraints over variables , which is solved by constraint satisfaction methods.

  7. Competitive Lotka–Volterra equations - Wikipedia

    en.wikipedia.org/wiki/Competitive_Lotka...

    This model can be generalized to any number of species competing against each other. One can think of the populations and growth rates as vectors, α 's as a matrix.Then the equation for any species i becomes = (=) or, if the carrying capacity is pulled into the interaction matrix (this doesn't actually change the equations, only how the interaction matrix is defined), = (=) where N is the ...

  8. Strassen algorithm - Wikipedia

    en.wikipedia.org/wiki/Strassen_algorithm

    This reduces the number of matrix additions and subtractions from 18 to 15. The number of matrix multiplications is still 7, and the asymptotic complexity is the same. [6] The algorithm was further optimised in 2017, [7] reducing the number of matrix additions per step to 12 while maintaining the number of matrix multiplications, and again in ...

  9. Balanced matrix - Wikipedia

    en.wikipedia.org/wiki/Balanced_matrix

    Equivalent to the definition, a 0-1 matrix is balanced if and only if it does not contain a submatrix that is the incidence matrix of any odd cycle (a cycle graph of odd order). [2] Therefore, the only three by three 0-1 matrix that is not balanced is (up to permutation of the rows and columns) the following incidence matrix of a cycle graph of ...