We study hyper-decoherence in three operational theories from the literature, all examples of recently introduced higher-order CPM construction. Amongst these, we show theory density hypercubes to be richest terms post-quantum phenomena. Specifically, demonstrate existence a probabilistic quantum systems and calculate associated hyper-phase group. This makes significant foundational interest, a...

In many regards, tuning deep-learning networks is still more an art than it is a technique. Choosing the correct hyper-parameters and getting a complex network to learn properly can be daunting to people not well versed in that art. Taking the example of entailment classification, this work will analyze different methods and tools that can be used in order to diagnose learning problems. It will...

In this paper, we give method for probabilistic assignment to the Realistic Abduc-tive Reasoning Model, proposed in 1]. The knowledge is assumed to be represented in the form of causal chaining, namely, hyper-bipartite network. Hyper-bipartite network is the most generalized form of knowledge representation for which, so far, there has been no way of assigning the probability to the explanation...

The performance of an algorithm often largely depends on some hyper parameter which should be optimized before its usage. Since most conventional optimization methods suffer from some drawbacks, we developed an alternative way to find the best hyper parameter values. Contrary to the well known procedures, the new optimization algorithm is based on statistical methods since it uses a combination...

To discuss the management options of retained products of conception (RPOC) with increased vascularity where simple dilatation and curettage may lead to life threatening haemorrhage and endanger the life of the patient. We present a series of three cases that had RPOC with hyper vascularity and were managed with different approaches. A brief review of management options is discussed. Out of thr...

An application of iterative methods for computing the Moore–Penrose inverse in balancing chemical equations is considered. With the aim to illustrate proposed algorithms, an improved high order hyper-power matrix iterative method for computing generalized inverses is introduced and applied. The improvements of the hyper-power iterative scheme are based on its proper factorization, as well as on...

IV jPhaseFit: the fitting module 5 IV-A Abstract Classes . . . . . . . . . . . . . . . . . . . . . . . . . 6 IV-B Concrete Classes: Maximum Likelihood Algorithms . . . . . . . 6 IV-B.1 General Phase-Type Distribution EM Algorithm [1] . . 6 IV-B.2 Hyper-Exponential Distribution EM Algorithm [2] . . . 7 IV-B.3 Hyper-Erlang Distribution EM Algorithm [3] . . . . . 7 IV-C Concrete Classes: Moment Ma...

The Covariance Matrix Adaptation Evolution Strategy (CMAES) is widely accepted as a robust derivative-free continuous optimization algorithm for non-linear and non-convex optimization problems. CMA-ES is well known to be almost parameterless, meaning that only one hyper-parameter, the population size, is proposed to be tuned by the user. In this paper, we propose a principled approach called se...

Virginia Kiryakova Dedicated to the 75th anniversary of Professor Gary Roach Abstract A generalization of the Poisson-type integral transformation proposed by Dimovski is applied to hyper-Bessel differential equations of arbitrary order, as a transmutation operator. By this method, their solutions are written in an explicit form, by evaluating operators of the generalized fractional calculus of...

Hyperbolicity measures, in terms of (distance) metrics, how close a given graph is to being a tree. Due to its relevance in modeling real-world networks, hyperbolicity has seen intensive research over the last years. Unfortunately, the best known algorithms for computing the hyperbolicity number of a graph (the smaller, the more tree-like) have running time O(n), where n is the number of graph ...