minimax techniques/ linear-time algorithmminmax-regret versioncontinuous unbounded knapsack problemuncertain objective function coefficientsoptimization problempolynomial algorithm/ C1290 Applications of systems
Furthermore, in [3] a two-phase scaled penalty type algorithm is presented for general nonlinear programs. The first phase finds an approximate feasible point, while the second phase involves generating apTaylor approximation of a quadratic penalty function and the next iterate is the solution that...
We investigate the problem of equilibrium computation for “large”n-player games. Large games have a Lipschitz-type property that no single player’s utility is greatly affected by any other individual player’s actions. In this paper, we mostly focus on the case where any change of strategy ...
is an assignment of truth values to the variables of the expression such that the expression evaluates to ’true’, then a nondeterministic computer is able to verify that in polynomial time. In the first few steps it correctly guesses that assignment, and then by a deterministic algorithmit...
To this end, we fix a flaw in the parameterized algorithm given by Misra et al. [AAMAS 2015], which uses the Hamming distance upper-bound as parameter. Moreover, we prove that on both linear and partial orders, it is W[2]-hard to determine the winners with respect to the size of ...
The consistency of such data is crucial and any potential sources of bias, such as how the dose distribution is normalised [6], [7], [8] and what calculation algorithm and dose quantity is used [9] should be carefully considered and reported. The evaluation of the calculated dose ...
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code. - minimaxir/textgenrnn
Then the minimax function for F is defined as MM(f) = min p max x,y,f(x) =f(y) 1 i:x i =y i p x (i)p y (i) ≤ max x,y,f(x) =f(y) 1 i:x i =y i p x (i)p y (i) Any quantum query algorithm requires at least Ω(MM(f)) queries [7]. Suppose we...
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Step (1), on the other hand, is extremely interesting; it requires us to prove lower bounds in a new model of algebraic query complexity. In this model, an algorithm is given oracle access to a Boolean function A : {0, 1}n → {0, 1}. It is trying to answer some question about...