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Information geometry is a study of statistical manifolds, that is, spaces of probability distributions from a geometric perspective. Its classical information-theoretic applications relate to statistical concepts such as Fisher information, sufficien
Externí odkaz:
http://arxiv.org/abs/2310.03884
Autor:
Gayen, Atin, Kumar, M. Ashok
Publikováno v:
IEEE Transactions on Information Theory 69 (12) 7565 - 7583 (2023)
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 al. likelihood functions that are popular among distance-based robust
Externí odkaz:
http://arxiv.org/abs/2205.00530
Autor:
S, Uma Maheswari, Alphy, Anna, Deivasikamani, Ganeshkumar, Prakash, U., Shadrach, Finney Daniel, Kumar, M. Ashok, Manoj, S.
Publikováno v:
In Groundwater for Sustainable Development May 2024 25
Autor:
Mishra, Kumar Vijay, Kumar, M. Ashok
We examine the role of information geometry in the context of classical Cram\'er-Rao (CR) type inequalities. In particular, we focus on Eguchi's theory of obtaining dualistic geometric structures from a divergence function and then applying Amari-Nag
Externí odkaz:
http://arxiv.org/abs/2104.01061
This paper establishes a close relationship among the four information theoretic problems, namely Campbell source coding, Arikan guessing, Huleihel et al. memoryless guessing and Bunte and Lapidoth tasks partitioning problems. We first show that the
Externí odkaz:
http://arxiv.org/abs/2012.13707
Generalized Bayesian Cram\'{e}r-Rao Inequality via Information Geometry of Relative $\alpha$-Entropy
Autor:
Mishra, Kumar Vijay, Kumar, M. Ashok
The relative $\alpha$-entropy is the R\'enyi analog of relative entropy and arises prominently in information-theoretic problems. Recent information geometric investigations on this quantity have enabled the generalization of the Cram\'{e}r-Rao inequ
Externí odkaz:
http://arxiv.org/abs/2002.04732
Autor:
Kumar, M. Ashok, Mishra, Kumar Vijay
We study the geometry of probability distributions with respect to a generalized family of Csisz\'ar $f$-divergences. A member of this family is the relative $\alpha$-entropy which is also a R\'enyi analog of relative entropy in information theory an
Externí odkaz:
http://arxiv.org/abs/2001.04769
Akademický článek
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Autor:
Bazeer Ahamed, Suseela Sellamuthu, Purushotam Naidu Karri, Inumarthi V. Srinivas, A.N. Mohammed Zabeeulla, M. Ashok Kumar
Publikováno v:
Measurement: Sensors, Vol 30, Iss , Pp 100928- (2023)
Advances in health-related behaviors, technical breakthroughs, and the spread of healthy living activities have expanded personal health evaluation on a broad scale. In medical applications, networks, data, and communication systems are extensively u
Externí odkaz:
https://doaj.org/article/4c179ed562a44dc99787a30e7c78cc2f
Publikováno v:
Measurement: Sensors, Vol 29, Iss , Pp 100877- (2023)
This research proposes an IoT based technique for predicting rainfall forecast in coastal regions using a deep reinforcement learning model. The proposed technique utilizes Long Short-Term Memory (LSTM) networks to capture the temporal dependencies b
Externí odkaz:
https://doaj.org/article/16362b1c829d43a0aeab288d9a8dfefd