| Lambda architecture for cost-effective batch and speed big data processing M Kiran, P Murphy, I Monga, J Dugan, SS Baveja 2015 IEEE international conference on big data (big data), 2785-2792, 2015 | 351 | 2015 |
| FLAME: simulating large populations of agents on parallel hardware architectures M Kiran, P Richmond, M Holcombe, LS Chin, D Worth, C Greenough Proceedings of the 9th International Conference on Autonomous Agents and …, 2010 | 141 | 2010 |
| Modelling complex biological systems using an agent-based approach M Holcombe, S Adra, M Bicak, S Chin, S Coakley, AI Graham, J Green, ... Integrative Biology 4 (1), 53-64, 2012 | 89 | 2012 |
| Controlling distributed energy resources via deep reinforcement learning for load flexibility and energy efficiency S Touzani, AK Prakash, Z Wang, S Agarwal, M Pritoni, M Kiran, R Brown, ... Applied Energy 304, 117733, 2021 | 81 | 2021 |
| Security risks and their management in cloud computing AU Khan, M Oriol, M Kiran, M Jiang, K Djemame 4th IEEE International Conference on Cloud Computing Technology and Science …, 2012 | 77 | 2012 |
| Enabling intent to configure scientific networks for high performance demands M Kiran, E Pouyoul, A Mercian, B Tierney, C Guok, I Monga Future Generation Computer Systems 79, 205-214, 2018 | 72 | 2018 |
| A risk assessment framework and software toolkit for cloud service ecosystems K Djemame, D Armstrong, M Kiran, M Jiang Cloud computing 5, 119-126, 2011 | 68 | 2011 |
| Failover strategy for fault tolerance in cloud computing environment B Mohammed, M Kiran, KM Maiyama, MM Kamala, IU Awan Software: Practice and Experience 47 (9), 1243-1274, 2017 | 57 | 2017 |
| Large-scale modeling of economic systems M Holcombe, S Coakley, M Kiran, S Chin, C Greenough, D Worth, ... Complex Systems, 175-192, 2013 | 52 | 2013 |
| Cross-facility science with the superfacility project at lbnl B Enders, D Bard, C Snavely, L Gerhardt, J Lee, B Totzke, K Antypas, ... 2020 IEEE/ACM 2nd Annual Workshop on Extreme-scale Experiment-in-the-Loop …, 2020 | 48 | 2020 |
| Hyperparameter tuning for deep reinforcement learning applications M Kiran, M Ozyildirim arXiv preprint arXiv:2201.11182, 2022 | 45 | 2022 |
| Levenberg–Marquardt multi-classification using hinge loss function BM Ozyildirim, M Kiran Neural Networks 143, 564-571, 2021 | 38 | 2021 |
| A performance modeling framework for lambda architecture based applications M Gribaudo, M Iacono, M Kiran Future Generation Computer Systems 86, 1032-1041, 2018 | 36 | 2018 |
| Towards a service lifecycle based methodology for risk assessment in cloud computing M Kiran, M Jiang, DJ Armstrong, K Djemame 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure …, 2011 | 35 | 2011 |
| Biological synthesis of silver nanoparticles from marine alga Colpomenia sinuosa and its in vitro anti-diabetic activity DVK Manam, S Murugesan American Journal of Bio-pharmacology Biochemistry and Life Sciences (AJBBL …, 2014 | 34 | 2014 |
| Using machine learning for intent-based provisioning in high-speed science networks H Mahtout, M Kiran, A Mercian, B Mohammed Proceedings of the 3rd international workshop on systems and network …, 2020 | 31 | 2020 |
| Optimising fault tolerance in real-time cloud computing IaaS environment B Mohammed, M Kiran, IU Awan, KM Maiyama 2016 IEEE 4th international conference on future internet of things and …, 2016 | 30 | 2016 |
| Analysis of cloud test beds using opensource solutions B Mohammed, M Kiran 2015 3rd International Conference on Future Internet of Things and Cloud …, 2015 | 28 | 2015 |
| Classifying elephant and mice flows in high-speed scientific networks A Chhabra, M Kiran Proc. INDIS, 1-8, 2017 | 27 | 2017 |
| Legal issues in clouds: towards a risk inventory K Djemame, B Barnitzke, M Corrales, M Kiran, M Jiang, D Armstrong, ... Philosophical Transactions of the Royal Society A: Mathematical, Physical …, 2013 | 27 | 2013 |
Inder MongaESnet/ Lawrence Berkeley National LabПотвърден имейл адрес: lbl.gov
