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Stochastic entrainment of a stochastic oscillator
Physical Review E, 2015 In this work, we consider a stochastic oscillator described by a discrete-state continuous-time Markov chain, in which the states are arranged in a circle, and there is a constant probability per unit time of jumping from one state to the next in a specified direction around the circle.
Guanyu, Wang, Charles S, Peskin
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Stochastic Synthesis for Stochastic Computing
CoRR, 2018 Stochastic computing (SC) is an emerging computing technique which offers higher computational density, and lower power over binary-encoded (BE) computation. Unlike BE computation, SC encodes values as probabilistic bitstreams which makes designing new circuits unintuitive.
Vincent T. Lee +3 more
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Stochastic programming approaches to stochastic scheduling [PDF]
Journal of Global Optimization, 1996 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
John R. Birge, Michael A. H. Dempster
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A toolbox to demystify probabilistic and statistical paradoxes
Frontiers in Education, 2023 There is a variety of empirical evidence that the coverage of paradoxes in mathematics education helps to support thorough understanding of probabilistic and statistical concepts.
Riko Kelter +2 more
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Stochastic counterfactuals and stochastic sufficient causes [PDF]
Statistica Sinica, 2012 Most work in causal inference concerns deterministic counterfactuals; the literature on stochastic counterfactuals is small. In the stochastic counterfactual setting, the outcome for each individual under each possible set of exposures follows a probability distribution so that for any given exposure combination, outcomes vary not only between ...
Tyler J, Vanderweele, James M, Robins
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Energies, 2020 Thermochemical Energy Storage (TCES), specifically the calcium oxide (CaO)/calcium hydroxide (Ca(OH)2) system is a promising energy storage technology with relatively high energy density and low cost. However, the existing models available to predict the
Timothy Praditia +3 more
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BMC Bioinformatics, 2022 Background Identifying drug–target interactions (DTIs) plays a key role in drug development. Traditional wet experiments to identify DTIs are expensive and time consuming. Effective computational methods to predict DTIs are useful to narrow the searching
Junjun Zhang, Minzhu Xie
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Stochastic Apportionment [PDF]
The American Mathematical Monthly, 2004 The problem of how to allocate to states the seats in the US House of Representatives is the most studied instance of what is termed the `apportionment problem'. We propose a new method of apportionment which is stochastic, which meets the quota condition, and which is fair in the sense of expectations.
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Stochastic-Constrained Stochastic Optimization with Markovian Data
J. Mach. Learn. Res., 2023 This paper considers stochastic-constrained stochastic optimization where the stochastic constraint is to satisfy that the expectation of a random function is below a certain threshold. In particular, we study the setting where data samples are drawn from a Markov chain and thus are not independent and identically distributed.
Yeongjong Kim, Dabeen Lee
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Proceedings of the AAAI Conference on Artificial Intelligence, 2014 Online services such as web search and e-commerce applications typically rely on the collection of data about users, including details of their activities on the web. Such personal data is used to maximize revenues via targeting of advertisements and longer engagements of users, and to enhance the quality of service via personalization
Adish Singla +3 more
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