4 citations · 10 across the 9 of their papers we have counts for
13 papers
Information Geometry for the Working Information Theorist
Kumar Vijay Mishra, M. Ashok Kumar, Ting-Kam Leonard Wong
Information geometry is a study of statistical manifolds, that is, spaces of probability distributions from a geometric perspective. Its classical information-theoretic application…
Generalized Fisher-Darmois-Koopman-Pitman Theorem and Rao-Blackwell Type Estimators for Power-Law Distributions
Atin Gayen, M. Ashok Kumar
This paper generalizes the notion of sufficiency for estimation problems beyond maximum likelihood. In particular, we consider estimation problems based on Jones et al. and Basu et…
Information Geometry and Classical Cramér-Rao Type Inequalities
Kumar Vijay Mishra, M. Ashok Kumar
We examine the role of information geometry in the context of classical Cramér-Rao (CR) type inequalities. In particular, we focus on Eguchi's theory of obtaining dualistic geometr…
Are Guessing, Source Coding, and Tasks Partitioning Birds of a Feather?
M. Ashok Kumar, Albert Sunny, Ashish Thakre +2
This paper establishes a close relationship among the four information theoretic problems, namely Campbell source coding, Arikan guessing, Huleihel et al. memoryless guessing and B…
Cramér-Rao Lower Bounds Arising from Generalized Csiszár Divergences
M. Ashok Kumar, Kumar Vijay Mishra
We study the geometry of probability distributions with respect to a generalized family of Csiszár -divergences. A member of this family is the relative -entropy which is als…
A Unified Framework for Problems on Guessing, Source Coding and Task Partitioning
M. Ashok Kumar, Albert Sunny, Ashish Thakre +1
We study four problems namely, Campbell's source coding problem, Arikan's guessing problem, Huieihel et al.'s memoryless guessing problem, and Bunte and Lapidoth's task partitionin…