Zobrazeno 1 - 10
of 56
pro vyhledávání: '"Nandyala Hemachandra"'
Publikováno v:
EAI Endorsed Transactions on Internet of Things, Vol 1, Iss 3 (2015)
This paper identifies two different parametrized dynamic priority queue disciplines, earliest due date (EDD) based and head of line priority jump (HOL-PJ), which are found to be mean waiting time complete in two class M/G/1 queue. An explicit one-to-
Externí odkaz:
https://doaj.org/article/8b452f93d9a3469396018b5d152f6ed5
Publikováno v:
European Journal of Operational Research. 310:249-267
This paper considers the problem of finding near-optimal Markovian randomized (MR) policies for finite-state-action, infinite-horizon, constrained risk-sensitive Markov decision processes (CRSMDPs). Constraints are in the form of standard expected di
Publikováno v:
Queueing Systems. 96:245-284
Queues can be seen as a service facility where quality of service (QoS) is an important measure for the performance of the system. In many cases, the queue implements the optimal admission control (either discounted or average) policy in the presence
Publikováno v:
ACM Transactions on Modeling and Performance Evaluation of Computing Systems. 5:1-37
Completeness of a dynamic priority scheduling scheme is of fundamental importance for the optimal control of queues in areas as diverse as computer communications, communication networks, supply/value chains, and manufacturing systems. Our first main
Autor:
Sherief Abdulla, Josh Agarwal, K.N. Apinaya Prethi, Parth Arora, Ananya Banerjee, Ketaki Barde, Shailesh Pramod Bendale, Lamia Berkani, Robin Singh Bhadoria, Ajay Kumar Bharti, Shobhit Bhatnagar, Naman Bhoj, Nilesh Chandra, Santosh L. Deshpande, Anuj Diwedi, Rahul Kumar Dubey, Imo J. Eyoh, A. Ganesan, Ashray Gupta, Manu K. Gupta, Marjan Gusev, Rajeswary Hari, U. Hariharan, Mohd Haroon, null Harshvardhan, Nandyala Hemachandra, Shashi Jain, G.O. Jijina, A. Kalaivani, Rohit B. Kaliwal, N. Kanimozhi, N. Kanya, Ramgopal Kashyap, Harsh Kashyap, Imene Lydia Kerboua, Param Khakhar, Santosh Kumar, Swarup Kumar, Michael Manry, Elezabeth Mathew, Eesha Mishra, Vadivel S. Murugesan, G. Nalinashini, S. Nithya, Megha Nivurruti, Emmanuel E. Nyoho, Vipin Pal, Rajiv Pandey, Dharmendra Pathak, Anju S. Pillai, R.S. Ponmagal, Jayashree Rajesh Prasad, Rajesh Shardanand Prasad, Boppuru Rudra Prathap, Surendra Rahamatkar, K. Rajkumar, Chinmay Rane, Archana Sahai, M. Sangeetha, Vijayalakshmi Saravanan, Rahul Saxena, S. Sendilvelan, Shambhavi Sharma, R. Shree Charran, Zeeshan Ali Siddiqui, Mukul Singh, Vaishali Singh, P. Solainayagi, Raghavendra Sriram, K. Sujatha, Ashish Tiwari, Kanishka Tyagi, Uduak A. Umoh, Isaac Woungang, Anju Yadav, Sofiane Zeghoud
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::317f6365f41952b7625636e75511f880
https://doi.org/10.1016/b978-0-12-824054-0.09992-5
https://doi.org/10.1016/b978-0-12-824054-0.09992-5
Publikováno v:
Computer Communications. 148:27-41
We consider the well-known wireless fair opportunistic schedulers (mainly the alpha-fair schedulers) and analyze their price of fairness (PoF). Efficient scheduler, designed from the system perspective, maximizes the sum of accumulated utilities of a
Autor:
Prashant Trivedi, Nandyala Hemachandra
Multi-agent actor-critic algorithms are an important part of the Reinforcement Learning paradigm. We propose three fully decentralized multi-agent natural actor-critic (MAN) algorithms in this work. The objective is to collectively find a joint polic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::33d3311e3467bda8b8b99c2426c0ed84
http://arxiv.org/abs/2109.01654
http://arxiv.org/abs/2109.01654
Publikováno v:
COMSNETS
In medical diagnosis, physicians predict the state of a patient by checking measurements (features) obtained from a sequence of tests, e.g., blood test, urine test, followed by invasive tests. As tests are often costly, one would like to obtain only
Publikováno v:
AAAI
We consider the problem of learning linear classifiers when both features and labels are binary. In addition, the features are noisy, i.e., they could be flipped with an unknown probability. In Sy-De attribute noise model, where all features could be