Part 2: Machine LearningInternational audienceThe limitations of Shannon information theory are pointed out from new perspectives. The limitations mainly exist in the neglects of the information reliability and completeness. The significances of the information reliability to the information measurements are further illustrated through example analysis. It is pointed out that such limitations originate from neglects of multi-level information uncertainties, uncertainty of the model and other objects of information system, and insufficient knowledge on uncertainties of probability values
Abstract—In this paper, a mathematical theory of learning is proposed that has many parallels with i...
Despite of its formal precision and its great many applications, Shannon’s theory still offers an ac...
Information theoretical measures are used to design, from first principles, an objective function th...
1st International Electronic Conference on Information IECI2021, online, December 2021International ...
Inference is expressed using information and is therefore subject to the limitations of information....
There are (at least) three approaches to quantifying information. The first, algorithmic information...
Machine learning is widely regarded as a tool for overcoming the bottleneck in knowledge acquisition...
Shannon's mathematical theory of communication defines fundamental limits on how much information ca...
Volume 1 : The volume “Storing and Transmitting Data” is based on Rudolf Ahlswede's introductory cou...
Information is the reduction of uncertainty. Imagine your friend invites you to dinner for the first...
This English version of Ruslan L. Stratonovich’s Theory of Information (1975) builds on theory and p...
In Phys. Rev. A 63 022113 (2001), Brukner and Zeilinger claim that the Shannon information is not we...
The information content of a source is defined in terms of the minimum number of bits needed to stor...
This dissertation illustrates how certain information-theoretic ideas and views on learning problems...
This book presents tools and principles of information theory as a solution to analyse insufficient i...
Abstract—In this paper, a mathematical theory of learning is proposed that has many parallels with i...
Despite of its formal precision and its great many applications, Shannon’s theory still offers an ac...
Information theoretical measures are used to design, from first principles, an objective function th...
1st International Electronic Conference on Information IECI2021, online, December 2021International ...
Inference is expressed using information and is therefore subject to the limitations of information....
There are (at least) three approaches to quantifying information. The first, algorithmic information...
Machine learning is widely regarded as a tool for overcoming the bottleneck in knowledge acquisition...
Shannon's mathematical theory of communication defines fundamental limits on how much information ca...
Volume 1 : The volume “Storing and Transmitting Data” is based on Rudolf Ahlswede's introductory cou...
Information is the reduction of uncertainty. Imagine your friend invites you to dinner for the first...
This English version of Ruslan L. Stratonovich’s Theory of Information (1975) builds on theory and p...
In Phys. Rev. A 63 022113 (2001), Brukner and Zeilinger claim that the Shannon information is not we...
The information content of a source is defined in terms of the minimum number of bits needed to stor...
This dissertation illustrates how certain information-theoretic ideas and views on learning problems...
This book presents tools and principles of information theory as a solution to analyse insufficient i...
Abstract—In this paper, a mathematical theory of learning is proposed that has many parallels with i...
Despite of its formal precision and its great many applications, Shannon’s theory still offers an ac...
Information theoretical measures are used to design, from first principles, an objective function th...