Parameterized beyond-Einstein growth
نویسندگان
چکیده
منابع مشابه
Framing the Health Workforce Agenda Beyond Economic Growth
The fourth Global Forum on Human Resources (HRH) for Health was held in Ireland November 2017. Its Dublin declaration mentions that strategic investments in the health workforce could contribute to sustainable and inclusive growth and are an imperative to shared prosperity. What is remarkable about the investment frame for health workforce development is that there is little debate about the ty...
متن کاملThe Parameterized Complexity of Reasoning Problems Beyond NP
Today’s propositional satisfiability (SAT) solvers are extremely powerful and can be used as an efficient back-end for solving NP-complete problems. However, many fundamental problems in knowledge representation and reasoning are located at the second level of the Polynomial Hierarchy or even higher, and hence polynomial-time transformations to SAT are not possible, unless the hierarchy collaps...
متن کاملMachine Characterizations for Parameterized Complexity Classes Beyond Para-NP
Due to the remarkable power of modern SAT solvers, one can efficiently solve NP-complete problems in many practical settings by encoding them into SAT. However, many important problems in various areas of computer science lie beyond NP, and thus we cannot hope for polynomial-time encodings into SAT. Recent research proposed the use of fixed-parameter tractable (fpt) reductions to provide effici...
متن کاملBeyond Bidimensionality: Parameterized Subexponential Algorithms on Directed Graphs
In 2000 Alber et al. [SWAT 2000 ] obtained the first parameterized subexponential algorithm on undirected planar graphs by showing that k-DOMINATING SET is solvable in time 2O( √ k)nO(1), where n is the input size. This result triggered an extensive study of parameterized problems on planar and more general classes of sparse graphs and culminated in the creation of Bidimensionality Theory by De...
متن کاملBeyond Fuzzy: Parameterized Approximations of Heyting Algebras for Uncertain Knowledge
We propose a parameterized framework based on a Heyting algebra and Lukasiewicz negation for modeling uncertainty for belief. We adopt a probability theory as mathematical formalism for manipulating uncertainty. An agent can express the uncertainty in her knowledge about a piece of information in the form of belief types: as a single probability, as an interval (lower and upper boundary for a p...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Astroparticle Physics
سال: 2007
ISSN: 0927-6505
DOI: 10.1016/j.astropartphys.2007.09.003