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Statistical and computational methods are widely used in today's scientific studies. Using a female fertility potential in childhood cancer survivors as an example, we illustrate how these methods can be used to extract insight regarding…

Applications · Statistics 2020-11-20 L. Yu , Z. Lu , P. C. Nathan , S. Mostoufi-Moab , Y. Yuan

This paper investigates the stakes of introducing probabilistic approaches for the management of power system's security. In real-time operation, the aim is to arbitrate in a rational way between preventive and corrective control, while…

Systems and Control · Computer Science 2016-02-18 Efthymios Karangelos , Patrick Panciatici , Louis Wehenkel

Quantitative characterizations and estimations of uncertainty are of fundamental importance in optimization and decision-making processes. Herein, we propose intuitive scores, which we call certainty and doubt, that can be used in both a…

Quantum computing provides a powerful framework for tackling computational problems that are classically intractable. The goal of this paper is to explore the use of quantum computers for solving relevant problems in systems and control…

Systems and Control · Electrical Eng. & Systems 2025-12-23 Jan Schneider , Julian Berberich

Mortality risk is a major concern to patients have just been discharged from the intensive care unit (ICU). Many studies have been directed to construct machine learning models to predict such risk. Although these models are highly…

Applications · Statistics 2021-01-20 Eugene T. Y. Ang , Milashini Nambiar , Yong Sheng Soh , Vincent Y. F. Tan

An observer-based Hamiltonian identification algorithm for quantum systems is proposed. For the 2-level case an exponential convergence result based on averaging arguments and some relevant transformations is provided. The convergence for…

Mathematical Physics · Physics 2007-05-23 Mazyar Mirrahimi , Pierre Rouchon

This paper studies online algorithms augmented with multiple machine-learned predictions. While online algorithms augmented with a single prediction have been extensively studied in recent years, the literature for the multiple predictions…

Machine Learning · Computer Science 2022-07-14 Keerti Anand , Rong Ge , Amit Kumar , Debmalya Panigrahi

I assess the potential of quantum computation. Broad and important applications must be found to justify construction of a quantum computer; I review some of the known quantum algorithms and consider the prospects for finding new ones.…

Quantum Physics · Physics 2009-10-30 John Preskill

In this article, we use the illness-death model to present a mathematical framework for studying the compression of morbidity (COM) hypothesis. It turns out that questions about COM are completely determined by the transition rates in the…

Quantitative Methods · Quantitative Biology 2018-07-31 Ralph Brinks

Time evolution of quantum systems is of interest in physics, in chemistry, and, more recently, in computer science. Quantum computers are suggested as one route to propagating quantum systems far more efficiently than ordinary numerical…

Quantum Physics · Physics 2015-02-13 James Daniel Whitfield

We propose a probabilistic mortality forecasting model that can be applied to derive forecasts for populations with regular and irregular mortality developments. Our model (1) uses rates of mortality improvement to model dynamic age…

Applications · Statistics 2014-01-14 Christina Bohk , Roland Rau

In this work we check the occurrence of the Azbel assumption of mortality within the framework of a bit string model for biological ageing. We reproduced the observed feature of linear correspondence between the fitting parameters of the…

adap-org · Physics 2008-02-03 A. Racco , M. Argollo de Menezes , T. J. P. Penna

The application of routing algorithms to real-world situations is a widely studied research topic. Despite this, routing algorithms and applications are usually developed for a general purpose, meaning that certain groups, such as ageing…

Artificial Intelligence · Computer Science 2023-11-21 Andoni Aranguren , Eneko Osaba , Silvia Urra-Uriarte , Patricia Molina-Costa

Lifelong machine learning is a novel machine learning paradigm which can continually accumulate knowledge during learning. The knowledge extracting and reusing abilities enable the lifelong machine learning to solve the related problems.…

Computation and Language · Computer Science 2019-06-03 Xianbin Hong , Gautam Pal , Sheng-Uei Guan , Prudence Wong , Dawei Liu , Ka Lok Man , Xin Huang

Background: The rapid advancement of Machine Learning (ML) represents novel opportunities to enhance public health research, surveillance, and decision-making. However, there is a lack of comprehensive understanding of algorithmic bias,…

Machine Learning · Computer Science 2024-09-04 Shaina Raza , Arash Shaban-Nejad , Elham Dolatabadi , Hiroshi Mamiya

Risk assessment algorithms are being adopted by public sector agencies to make high-stakes decisions about human lives. Algorithms model "risk" based on individual client characteristics to identify clients most in need. However, this…

Human-Computer Interaction · Computer Science 2023-02-17 Devansh Saxena , Erina Seh-Young Moon , Aryan Chaurasia , Yixin Guan , Shion Guha

We analyze the computational power and limitations of the recently proposed 'quantum adiabatic evolution algorithm'.

Quantum Physics · Physics 2007-05-23 Wim van Dam , Michele Mosca , Umesh Vazirani

Quantum computers have attracted much attention in recent years. This is because the development of the actual quantum machine is accelerating. Research on how to use quantum computers is active in the fields such as quantum chemistry and…

Quantum Physics · Physics 2024-12-02 Kazumasa Ueno , Hiroaki Miura

Mortality forecasting plays a pivotal role in insurance and financial risk management of life insurers, pension funds, and social securities. Mortality data is usually high-dimensional in nature and favors factor model approaches to…

Applications · Statistics 2021-12-10 Lingyu He , Fei Huang , Yanrong Yang

Lifelong learning can be viewed as a continuous transfer learning procedure over consecutive tasks, where learning a given task depends on accumulated knowledge --- the so-called knowledge base. Most published work on lifelong learning…

Machine Learning · Statistics 2018-10-30 Changjian Shui , Ihsen Hedhli , Christian Gagné
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