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   https://doi.org/10.1109/CDC45484.2021.9683248  

   Poveda, Jorge I.; Krstic, Miroslav (December 2021, 2021 60th IEEE Conference on Decision and Control (CDC))
2. Polynomial-Time Axioms of Choice and Polynomial-Time Cardinality

   https://doi.org/10.1007/s00224-023-10118-y  

   Grochow, Joshua A. (May 2023, Theory of Computing Systems)

   Abstract There is no single canonical polynomial-time version of the Axiom of Choice (AC); several statements of AC that are equivalent in Zermelo-Fraenkel (ZF) set theory are already inequivalent from a constructive point of view, and are similarly inequivalent from a complexity-theoretic point of view. In this paper we show that many classical formulations of AC, when restricted to polynomial time in natural ways, are equivalent to standard complexity-theoretic hypotheses, including several that were of interest to Selman. This provides a unified view of these hypotheses, and we hope provides additional motivation for studying some of the lesser-known hypotheses that appear here. Additionally, because several classical forms of AC are formulated in terms of cardinals, we develop a theory of polynomial-time cardinality. Nerode & Remmel (Contemp. Math.106, 1990 and Springer Lec. Notes Math. 1432, 1990) developed a related theory, but restricted to unary sets. Downey (Math. Reviews MR1071525) suggested that such a theory over larger alphabets could have interesting connections to more standard complexity questions, and we illustrate some of those connections here. The connections between AC, cardinality, and complexity questions also allow us to highlight some of Selman’s work. We hope this paper is more of a beginning than an end, introducing new concepts and raising many new questions, ripe for further research. 

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3. Relativistic Real-Time Time-Dependent Equation-of-Motion Coupled-Cluster

   https://doi.org/10.1021/acs.jctc.9b00729  

   Koulias, Lauren N.; Williams-Young, David B.; Nascimento, Daniel R.; DePrince, A. Eugene; Li, Xiaosong (October 2019, Journal of Chemical Theory and Computation)
4. Real-time Forecasting of On-Time Performance in Metrorail Systems

   Soper, Robert; Flowers, Bryse; Bijinemula, Sandeep; Mayer, Brian; Khaghani, Farnaz; Holt, Jordan; Ramakrishnan, Naren (January 2018, 7th SIGKDD International Workshop on Urban Computing (UrbComp 2018))
5. Semiparametric estimation of structural failure time models in continuous-time processes

   https://doi.org/10.1093/biomet/asz057  

   Yang, S; Pieper, K; Cools, F (October 2019, Biometrika)

   Summary Structural failure time models are causal models for estimating the effect of time-varying treatments on a survival outcome. G-estimation and artificial censoring have been proposed for estimating the model parameters in the presence of time-dependent confounding and administrative censoring. However, most existing methods require manually pre-processing data into regularly spaced data, which may invalidate the subsequent causal analysis. Moreover, the computation and inference are challenging due to the nonsmoothness of artificial censoring. We propose a class of continuous-time structural failure time models that respects the continuous-time nature of the underlying data processes. Under a martingale condition of no unmeasured confounding, we show that the model parameters are identifiable from a potentially infinite number of estimating equations. Using the semiparametric efficiency theory, we derive the first semiparametric doubly robust estimators, which are consistent if the model for the treatment process or the failure time model, but not necessarily both, is correctly specified. Moreover, we propose using inverse probability of censoring weighting to deal with dependent censoring. In contrast to artificial censoring, our weighting strategy does not introduce nonsmoothness in estimation and ensures that resampling methods can be used for inference. 

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