Zobrazeno 1 - 10
of 2 624
pro vyhledávání: '"P. Vidyasagar"'
Autor:
Ferracina, Fabiana, Krishnamoorthy, Bala, Halappanavar, Mahantesh, Hu, Shengwei, Sathuvalli, Vidyasagar
We explore the application of machine learning algorithms to predict the suitability of Russet potato clones for advancement in breeding trials. Leveraging data from manually collected trials in the state of Oregon, we investigate the potential of a
Externí odkaz:
http://arxiv.org/abs/2404.03701
Autor:
Karandikar, Rajeeva L., Vidyasagar, M.
In this paper, we study the convergence properties of the Stochastic Gradient Descent (SGD) method for finding a stationary point of a given objective function $J(\cdot)$. The objective function is not required to be convex. Rather, our results apply
Externí odkaz:
http://arxiv.org/abs/2312.02828
Publikováno v:
Journal of Eating Disorders, Vol 12, Iss 1, Pp 1-11 (2024)
Abstract Background Higher prevalence of disordered eating in young adults with type 1 diabetes (T1D) culminates in higher levels of morbidity and mortality. In addition to validated questionnaires for diabetes distress, depression/anxiety symptoms a
Externí odkaz:
https://doaj.org/article/a68d44032a0e42619020929f0d945fa4
Autor:
G. Vinaya Chandu Vidyasagar, P. V. Janardhan Reddy, M. Md. Ghouse, T. C. Venkateswarulu, P. B. Kavi Kishor, Prashanth Suravajhala, Rathnagiri Polavarapu
Publikováno v:
AMB Express, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Corona virus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), claimed millions globally. After the report of the first incidence of the virus, variants emerged with each posing a unique
Externí odkaz:
https://doaj.org/article/e0b5fee8148444f9809373a7d56b2600
Autor:
Vidyasagar, Mathukumalli
In this paper, we present a brief survey of Reinforcement Learning (RL), with particular emphasis on Stochastic Approximation (SA) as a unifying theme. The scope of the paper includes Markov Reward Processes, Markov Decision Processes, Stochastic App
Externí odkaz:
http://arxiv.org/abs/2304.00803
In this paper, we study the well-known "Heavy Ball" method for convex and nonconvex optimization introduced by Polyak in 1964, and establish its convergence under a variety of situations. Traditionally, most algorithms use "full-coordinate update," t
Externí odkaz:
http://arxiv.org/abs/2303.16241
Autor:
Yeh, Eric, Hitaj, Briland, Sadhu, Vidyasagar, Roy, Anirban, Nakabayashi, Takuma, Tsuji, Yoshito
The recent explosion of high-quality image-to-image methods has prompted interest in applying image-to-image methods towards artistic and design tasks. Of interest for architects is to use these methods to generate design proposals from conceptual sk
Externí odkaz:
http://arxiv.org/abs/2303.11483
Publikováno v:
Asian Journal of Medical Sciences, Vol 15, Iss 6, Pp 76-80 (2024)
Background: Neonatal sepsis is a leading cause of neonatal morbidity and mortality globally, with variations in causative bacteria and treatment efficacy across health-care facilities. Aims and Objectives: The aims and objectives of the study are
Externí odkaz:
https://doaj.org/article/fcdf55cc45f34d30a6aa4ae88260b110
Autor:
Rishabh Sharma, Jasdeep Kaur Gill, Caitlin Carter, Wajd Alkabbani, Manik Chhabra, Kota Vidyasagar, Feng Chang, Linda Lee, Tejal Patel
Publikováno v:
Biomedicine Hub, Vol 9, Iss 1, Pp 83-88 (2024)
Introduction: Older adults with dementia who are on multiple medications are more vulnerable to the use of potentially inappropriate medications (PIMs), which can significantly increase the risk of adverse events and drug-related problems. PIMs use i
Externí odkaz:
https://doaj.org/article/e32624e04ced42a28036b313c16913fa
We present an approach for autonomous sensor control for information gathering under partially observable, dynamic and sparsely sampled environments that maximizes information about entities present in that space. We describe our approach for the tas
Externí odkaz:
http://arxiv.org/abs/2211.01527