Results 31 to 40 of about 207,129 (274)
Data‐driven performance metrics for neural network learning
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri +2 more
wiley +1 more source
Стратегические решения и риск-менеджмент, 2015 The article deals with the financial analysis of the companies in bankruptcy proceedings. Using the principle of invariance of factors in predicting the functions of financial analysis, it was possible to assess the parameters and structure of the ...
A. V. Babanov
doaj +1 more source
No-Signalling Is Equivalent To Free Choice of Measurements [PDF]
Electronic Proceedings in Theoretical Computer Science, 2014 No-Signalling is a fundamental constraint on the probabilistic predictions made by physical theories. It is usually justified in terms of the constraints imposed by special relativity.
Samson Abramsky +2 more
doaj +1 more source
Teaching Theory of Probability and Statistics during the Covid-19 Emergency
Symmetry, 2020 The state of emergency caused by the covid-19 pandemic has shown that teaching at this time is not easy. Teachers have to make more use of distance education and students have to adapt to that.
A. Berkova, Radek Nemec
semanticscholar +1 more source
Conditional independence in max-linear Bayesian networks [PDF]
The Annals of Applied Probability, 2020 Motivated by extreme value theory, max-linear Bayesian networks have been recently introduced and studied as an alternative to linear structural equation models. However, for max-linear systems the classical independence results for Bayesian networks are
Carlos Am'endola +3 more
semanticscholar +1 more source
Probability Theory: An Advanced Course
, 1995 1 Introduction.- 1.1 Random Variables.- 1.2 Monotone Class Theorems.- 1.3 Expectations and Uniform Integrability.- 1.4 Independence.- 1.5 Convergence Concepts.- 1.6 Additional Exercises.- 2 Spaces of Probability Measures.- 2.1 The Prohorov Topology.- 2.2
V. S. Borkar
semanticscholar +1 more source
Free independence and the noncrossing partition lattice in dual-unitary quantum circuits [PDF]
Physical review BWe investigate details of the chaotic dynamics of dual-unitary quantum circuits by evaluating all $2k$-point out-of-time-ordered correlators. For the generic class of circuits, by writing the correlators as contractions of a class of quantum channels, we
H. Chen, Jonah Kudler-Flam
semanticscholar +1 more source
Advances in Mechanical Engineering, 2017 This study aims to identify and analyze risk factors affecting serious multi-fatality crashes using Bayesian networks. First, a Bayesian network structure was constructed based on expert experience and the Dempster–Shafer evidence theory.
Shengxue Zhu +3 more
doaj +1 more source
ON THE THIN PRACTICAL RATIONALITY AND ITS THICKENINGS
Problemos, 1998 The article starts with the introduction of the Lithuanian reader into the expected utility theory which is the core of the decision theory known under the name of the rational choice theory or by the name of the thin theory of practical rationality too.
Zenonas Norkus
doaj +16 more sources
On the Empirical Validity of Cumulative Prospect Theory: Experimental Evidence of Rank‐Independent Probability Weighting [PDF]
Econometrica, 2019 Cumulative Prospect Theory (CPT), the leading behavioral account of decisionmaking under uncertainty, avoids the dominance violations implicit in Prospect Theory (PT) by assuming that the probability weight applied to a given outcome depends on its ranking.
Charles Sprenger +2 more
openaire +5 more sources