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ORCIDSriram Kailasam
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2020 – today
- 2024
[j9]Jyoti
, Sriram Kailasam, Aleksey Buzmakov:
A scalable, distributed framework for significant subgroup discovery. Knowl. Based Syst. 284: 111335 (2024)- [j8]Md Arshad Jamal, Sriram Kailasam, Bhumanyu Goyal, Varun Singh:
DiGTreeS: a distributed resilient framework for generalized tree search. J. Supercomput. 80(10): 15006-15037 (2024) - 2023
- [j7]Abhigyan Khaund, Abhishek Mukesh Sharma, Abhishek Tiwari, Shashwat Garg, Sriram Kailasam:
RD-FCA: A resilient distributed framework for formal concept analysis. J. Parallel Distributed Comput. 179: 104710 (2023) - [j6]Muneeswaran Packiaraj, Sriram Kailasam:
HyPar-FCA+: an improved workload-aware elastic framework for FCA. J. Supercomput. 79(11): 11767-11796 (2023) - [c13]Jyoti, Sriram Kailasam, Aleksey Buzmakov:
ParaDiS: a Parallel and Distributed framework for Significant pattern mining. CCGridW 2023: 249-255 - 2022
- [j5]Muneeswaran Packiaraj, Sriram Kailasam:
HyPar-FCA: a distributed framework based on hybrid partitioning for FCA. J. Supercomput. 78(10): 12589-12620 (2022) - [c12]Ganesan Ponnuswami, Sriram Kailasam, Dileep Aroor Dinesh:
Evaluating Data-Parallel Distributed Training Strategies. COMSNETS 2022: 759-763 - 2021
- [c11]Saurabh Bansal, Sriram Kailasam, Sergei Obiedkov:
Approximate Computation of Exact Association Rules. ICFCA 2021: 107-122 - 2020
- [c10]Muneeswaran Packiaraj, Jyoti, Sriram Kailasam:
A Hybrid Partitioning Strategy for Distributed FCA. CLA 2020: 71-82 - [c9]Jyoti, Aleksey Buzmakov, Sriram Kailasam:
Towards Stable Significant Subgroup Discovery. CLA 2020: 287-292 - [c8]Ganesan Ponnuswami, Sriram Kailasam, Dileep Aroor Dinesh:
Event-Driven Data Pipeline for Network Management Systems. ICCCNT 2020: 1-6 - [c7]Merlin Sundar, Sriram Kailasam, Timothy A. Gonsalves:
Benchmarking Distributed Stream Processing Frameworks for Real Time Classical Machine Learning Applications. ICCCNT 2020: 1-7
2010 – 2019
- 2019
- [j4]Harisankar Haridas, Sriram Kailasam, Janakiram Dharanipragada:
Cloudy Knapsack Algorithm for Offloading Tasks from Large Scale Distributed Applications. IEEE Trans. Cloud Comput. 7(4): 949-963 (2019) - [c6]Naveksha Sood, Shruti Kaushik, Aditya Nigam, Sriram Kailasam, Dileep D., Varun Dutt:
Applications of Statistical and Machine Learning Time-Series Methods for Predicting Internet Usage. MLDM (2) 2019: 760-774 - 2018
- [c5]Shravan Patel, Umang Agarwal, Sriram Kailasam:
A Dynamic Load Balancing Scheme for Distributed Formal Concept Analysis. ICPADS 2018: 489-496 - 2014
- [j3]Janakiram Dharanipragada, Geeta Iyer, Sriram Kailasam:
Generate-map-reduce: An extension to map-reduce to support shared data and recursive computations. Concurr. Comput. Pract. Exp. 26(2): 561-585 (2014) - [j2]Sriram Kailasam, Prateek Dhawalia, S. J. Balaji, Geeta Iyer, Janakiram Dharanipragada:
Extending MapReduce across Clouds with BStream. IEEE Trans. Cloud Comput. 2(3): 362-376 (2014) - [c4]Prateek Dhawalia, Sriram Kailasam, Dharanipragada Janakiram:
Chisel++: handling partitioning skew in MapReduce framework using efficient range partitioning technique. DICT@HPDC 2014: 21-28 - [c3]Harisankar Haridas, Sriram Kailasam, Janakiram Dharanipragada:
Cloudy knapsack problems: An optimization model for distributed cloud-assisted systems. P2P 2014: 1-5 - 2013
- [j1]Sriram Kailasam, Nathan Gnanasambandam, Dharanipragada Janakiram, Naveen Sharma:
Optimizing Ordered Throughput Using Autonomic Cloud Bursting Schedulers. IEEE Trans. Software Eng. 39(11): 1564-1581 (2013) - [c2]Prateek Dhawalia, Sriram Kailasam, Dharanipragada Janakiram:
Chisel: A Resource Savvy Approach for Handling Skew in MapReduce Applications. IEEE CLOUD 2013: 652-660 - 2010
- [c1]Sriram Kailasam, Nathan Gnanasambandam, Dharanipragada Janakiram, Naveen Sharma:
Optimizing Service Level Agreements for Autonomic Cloud Bursting Schedulers. ICPP Workshops 2010: 285-294
Coauthor Index
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