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We derive a new variational principle for the quantum Fisher information leading to a simple iterative alternating algorithm, the convergence of which is proved. The case of a fixed measurement, i.e. the classical Fisher information, is…

Quantum Physics · Physics 2013-12-06 Katarzyna Macieszczak

Any act of problem-solving combines prior knowledge, local search, and a third element that is less often discussed: the extraction of information from search to update understanding. I propose a model of mathematical problem-solving as a…

History and Overview · Mathematics 2026-03-11 Asvin G

We extend in a natural way the operation of Turing machines to infinite ordinal time, and investigate the resulting supertask theory of computability and decidability on the reals. The resulting computability theory leads to a notion of…

Logic · Mathematics 2007-05-23 Joel David Hamkins , Andy Lewis

Iterative imputation is a popular tool to accommodate missing data. While it is widely accepted that valid inferences can be obtained with this technique, these inferences all rely on algorithmic convergence. There is no consensus on how to…

Computation · Statistics 2021-10-25 Hanne Ida Oberman , Stef van Buuren , Gerko Vink

The study of the fundamental limits of information systems is a central theme in information theory. Both the traditional analytical approach and the recently proposed computational approach have significant limitations, where the former is…

Information Theory · Computer Science 2022-05-04 Wenjing Chen , Chao Tian

We propose a logic of interactive proofs as a framework for an intuitionistic foundation for interactive computation, which we construct via an interactive analog of the Goedel-McKinsey-Tarski-Artemov definition of Intuitionistic Logic as…

Logic in Computer Science · Computer Science 2017-08-09 Simon Kramer

Independence-based (IB) assignments to Bayesian belief networks were originally proposed as abductive explanations. IB assignments assign fewer variables in abductive explanations than do schemes assigning values to all evidentially…

Artificial Intelligence · Computer Science 2013-02-28 Eugene Santos , Solomon Eyal Shimony

What is computable with limited resources? How can we verify the correctness of computations? How to measure computational power with precision? Despite the immense scientific and engineering progress in computing, we still have only…

Other Computer Science · Computer Science 2016-10-20 Attila Egri-Nagy

Data based judgments go into artificial intelligence applications but they undergo paradoxical reversal when seemingly unnecessary additional data is provided. Examples of this are Simpson's reversal and the disjunction effect where the…

Artificial Intelligence · Computer Science 2017-09-14 Subhash Kak

The Church-Turing thesis asserts that if a partial strings-to-strings function is effectively computable then it is computable by a Turing machine. In the 1930s, when Church and Turing worked on their versions of the thesis, there was a…

Logic in Computer Science · Computer Science 2019-01-16 Yuri Gurevich

The Turing machine is one of the simple abstract computational devices that can be used to investigate the limits of computability. In this paper, they are considered from several points of view that emphasize the importance and the…

Computational Complexity · Computer Science 2012-03-16 Yaroslav D. Sergeyev , Alfredo Garro

In the classic AGM belief revision theory, beliefs are static and do not change their own shape. For instance, if p is accepted by a rational agent, it will remain p to the agent. But such rarely happens to us. Often, when we accept some…

Artificial Intelligence · Computer Science 2016-01-28 Ryuta Arisaka

This paper contributes a novel embedding model which measures the probability of each belief $\langle h,r,t,m\rangle$ in a large-scale knowledge repository via simultaneously learning distributed representations for entities ($h$ and $t$),…

Artificial Intelligence · Computer Science 2015-05-25 Miao Fan , Qiang Zhou , Andrew Abel , Thomas Fang Zheng , Ralph Grishman

This paper introduces a new probabilistic model for online learning which dynamically incorporates information from stochastic gradients of an arbitrary loss function. Similar to probabilistic filtering, the model maintains a Gaussian…

Machine Learning · Statistics 2015-05-27 Pedro A. Ortega , Koby Crammer , Daniel D. Lee

Many scientific investigations require that the values of a set of model parameters are estimated using recorded data. In Bayesian inference, information from both observed data and prior knowledge is combined to update model parameters…

Methodology · Statistics 2024-09-17 Xuebin Zhao , Andrew Curtis

Quantum theory (QT) has been confirmed by numerous experiments, yet we still cannot fully grasp the meaning of the theory. As a consequence, the quantum world appears to us paradoxical. Here we shed new light on QT by being based on two…

Quantum Physics · Physics 2019-05-21 Alessio Benavoli , Alessandro Facchini , Marco Zaffalon

The intelligent reformulation or restructuring of a belief network can greatly increase the efficiency of inference. However, time expended for reformulation is not available for performing inference. Thus, under time pressure, there is a…

Artificial Intelligence · Computer Science 2013-04-05 John S. Breese , Eric J. Horvitz

The notion of computability is stable (i.e. independent of the choice of an indexing) over infinite-dimensional vector spaces provided they have a finite "tensorial dimension". Such vector spaces with a finite tensorial dimension permit to…

Computational Complexity · Computer Science 2015-05-18 Pablo Arrighi , Gilles Dowek

By nature, transmissible human knowledge is enumerable: every sentence, movie, audio record can be encoded in a sufficiently long string of 0's and 1's. The works of G\"odel, Turing and others showed that there are inherent limits and…

Other Computer Science · Computer Science 2020-01-30 Frédéric Prost

Can a physicist make only a finite number of errors in the eternal quest to uncover the law of nature? This millennium-old philosophical problem, known as inductive inference, lies at the heart of epistemology. Despite its significance to…

Machine Learning · Computer Science 2024-09-27 Zhou Lu
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