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Standard General L.P. Standard General L.P. is an American hedge fund headquartered in New York City. It was founded in 2007 by Soohyung "Soo" Kim and Nicholas Singer with seed capital from Reservoir Capital Group. Since 2013, Soo Kim has been the Managing Partner and Chief Investment Officer. [1]
The dual of a given linear program (LP) is another LP that is derived from the original (the primal) LP in the following schematic way: The objective direction is inversed – maximum in the primal becomes minimum in the dual and vice versa. The weak duality theorem states that the objective value of the dual LP at any feasible solution is ...
Karmarkar's algorithm is an algorithm introduced by Narendra Karmarkar in 1984 for solving linear programming problems. It was the first reasonably efficient algorithm that solves these problems in polynomial time. The ellipsoid method is also polynomial time but proved to be inefficient in practice. Denoting by the number of variables, m the ...
A covering LP is a linear program of the form: Minimize: b T y, subject to: A T y ≥ c, y ≥ 0, such that the matrix A and the vectors b and c are non-negative. The dual of a covering LP is a packing LP, a linear program of the form: Maximize: c T x, subject to: Ax ≤ b, x ≥ 0, such that the matrix A and the vectors b and c are non ...
Lagrangian mechanics describes a mechanical system as a pair (M, L) consisting of a configuration space M and a smooth function within that space called a Lagrangian. For many systems, L = T − V, where T and V are the kinetic and potential energy of the system, respectively. [3]
A system of linear inequalities defines a polytope as a feasible region. The simplex algorithm begins at a starting vertex and moves along the edges of the polytope until it reaches the vertex of the optimal solution. Polyhedron of simplex algorithm in 3D. The simplex algorithm operates on linear programs in the canonical form.
Convex optimization is a subfield of mathematical optimization that studies the problem of minimizing convex functions over convex sets (or, equivalently, maximizing concave functions over convex sets). Many classes of convex optimization problems admit polynomial-time algorithms, [1] whereas mathematical optimization is in general NP-hard.
In computing, a linear-feedback shift register ( LFSR) is a shift register whose input bit is a linear function of its previous state. The most commonly used linear function of single bits is exclusive-or (XOR). Thus, an LFSR is most often a shift register whose input bit is driven by the XOR of some bits of the overall shift register value.
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