ON THE NUMBER OF 2-HOOKS AND 3-HOOKS OF INTEGER PARTITIONS [PDF]
, 2022 Eleanor McSpirit, Kristen Scheckelhoff
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Risk‐aware safe reinforcement learning for control of stochastic linear systems
Asian Journal of Control, EarlyView.Abstract This paper presents a risk‐aware safe reinforcement learning (RL) control design for stochastic discrete‐time linear systems. Rather than using a safety certifier to myopically intervene with the RL controller, a risk‐informed safe controller is also learned besides the RL controller, and the RL and safe controllers are combined together ...
Babak Esmaeili +2 more
wiley +1 more source
A Guide to Bayesian Optimization in Bioprocess Engineering
Biotechnology and Bioengineering, EarlyView.ABSTRACT Bayesian optimization has become widely popular across various experimental sciences due to its favorable attributes: it can handle noisy data, perform well with relatively small data sets, and provide adaptive suggestions for sequential experimentation.
Maximilian Siska +5 more
wiley +1 more source
Zhongguo dianliTaking into account the spatiotemporal support capacity of new energy station black start, a target network optimization method for power system black-start zoning is proposed to improve unconventional security defense ability of the new power system ...
Ruixin WANG +5 more
doaj +1 more source
A generalized Hardy-Ramanujan formula for the number of restricted integer partitions [PDF]
, 2018 Tiefeng Jiang, Ke Wang
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Restricted Tweedie stochastic block models
Canadian Journal of Statistics, EarlyView.Abstract The stochastic block model (SBM) is a widely used framework for community detection in networks, where the network structure is typically represented by an adjacency matrix. However, conventional SBMs are not directly applicable to an adjacency matrix that consists of nonnegative zero‐inflated continuous edge weights.
Jie Jian, Mu Zhu, Peijun Sang
wiley +1 more source
Non-Conventional Limits of Random Sequences Related to Partitions of Integers [PDF]
, 2019 Jordan Stoyanov, Christophe Vignat
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Asymptotic properties of cross‐classified sampling designs
Canadian Journal of Statistics, EarlyView.Abstract We investigate the family of cross‐classified sampling designs across an arbitrary number of dimensions. We introduce a variance decomposition that enables the derivation of general asymptotic properties for these designs and the development of straightforward and asymptotically unbiased variance estimators.
Jean Rubin, Guillaume Chauvet
wiley +1 more source
Distribution of Squares and Hypothesis Verification in Odd Integer Partitions [PDF]
Александр Андреевич Самойлов
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Integer programming column generation: accelerating branch-and-price using a novel pricing scheme for finding high-quality solutions in set covering, packing, and partitioning problems [PDF]
, 2023 Stephen J. Maher, Elina Rönnberg
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