Accelerated series for universal constants, by the WZ method.
Acceleration of Le Bail fitting method on parallel platforms
Le Bail fitting method is procedure used in the applied crystallography mainly during the crystal structure determination. As in many other applications, there is a need for a great performance and short execution time. In this paper, we describe utilization of parallel computing for mathematical operations used in Le Bail fitting. We present an algorithm implementing this method with highlighted possible approaches to its aforementioned parallelization. Then, we propose a sample parallel version...
Accurate and online-efficient evaluation of the a posteriori error bound in the reduced basis method
The reduced basis method is a model reduction technique yielding substantial savings of computational time when a solution to a parametrized equation has to be computed for many values of the parameter. Certification of the approximation is possible by means of an a posteriori error bound. Under appropriate assumptions, this error bound is computed with an algorithm of complexity independent of the size of the full problem. In practice, the evaluation of the error bound can become very sensitive...
Adaptive constraint reduction for training support vector machines.
Addressing the stochastic nature of scientific computations via dynamic loop scheduling.
Advice Complexity and Barely Random Algorithms
Recently, a new measurement – the advice complexity – was introduced for measuring the information content of online problems. The aim is to measure the bitwise information that online algorithms lack, causing them to perform worse than offline algorithms. Among a large number of problems, a well-known scheduling problem, job shop scheduling with unit length tasks, and the paging problem were analyzed within this model. We observe some connections between advice complexity and randomization. Our...
Advice Complexity and Barely Random Algorithms
Recently, a new measurement – the advice complexity – was introduced for measuring the information content of online problems. The aim is to measure the bitwise information that online algorithms lack, causing them to perform worse than offline algorithms. Among a large number of problems, a well-known scheduling problem, job shop scheduling with unit length tasks, and the paging problem were analyzed within this model. We observe some connections between advice complexity and randomization....
ALBERT---Software for scientific computations and applications.
Algorithm 25. Discrete optimization by the method of Mao and Wallingford
Algorithm 26. Limit distribution of the number of items in the queueing system E₂/E₂/n
Algorithm 27. Statistical prediction by the method of harmonical weights
Algorithm 29. Solving systems of linear equations by Sokolov's method
Algorithm 30. The calculation of the minimum of a certain function of one variable
Algorithm 31. The calculation of the minimum of a certain function of several variables
Algorithm 32. Construction of polynomial values orthogonal on given set of one-dimensional variable
Algorithm 35. Calculation of measures of stochastical dependence
Algorithm 37. Solution of sparse linear equation systems
Algorithm 42. Enclosure of a point to the minimum spanning tree
Algorithm 43. Evaluation of an improper integral on a finite interval
Algorithm 48. Solving boundary value problems for the biharmonic equation by the method of summary representations