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2020 – today
- 2024
[c34]Pau-Chen Cheng
, Kevin Eykholt, Zhongshu Gu, Hani Jamjoom, K. R. Jayaram, Enriquillo Valdez, Ashish Verma:
DeTA: Minimizing Data Leaks in Federated Learning via Decentralized and Trustworthy Aggregation. EuroSys 2024: 219-235- [c33]Evelyn Duesterwald, Vatche Isahagian, K. R. Jayaram, Ritesh Kumar, Vinod Muthusamy, Punleuk Oum, Gegi Thomas, Praveen Venkateswaran:
A Conversational Assistant Framework for Automation. Middleware Industry 2024: 1-7 - 2023
- [c32]Rahul Atul Bhope, K. R. Jayaram, Nalini Venkatasubramanian, Ashish Verma, Gegi Thomas:
FLIPS: Federated Learning using Intelligent Participant Selection. Middleware 2023: 301-315 - [c31]Aurora González-Vidal, Alexander Isenko, K. R. Jayaram:
On Serving Image Classification Models. WOSC@Middleware 2023: 48-52 - [i10]Rahul Atul Bhope, K. R. Jayaram, Nalini Venkatasubramanian, Ashish Verma, Gegi Thomas:
FLIPS: Federated Learning using Intelligent Participant Selection. CoRR abs/2308.03901 (2023) - 2022
- [c30]K. R. Jayaram, Vinod Muthusamy, Gegi Thomas, Ashish Verma, Mark Purcell:
Adaptive Aggregation For Federated Learning. IEEE Big Data 2022: 180-185 - [c29]K. R. Jayaram, Ashish Verma, Gegi Thomas, Vinod Muthusamy:
Just-in-Time Aggregation for Federated Learning. MASCOTS 2022: 1-8 - [p3]K. R. Jayaram, Ashish Verma:
Private Parameter Aggregation for Federated Learning. Federated Learning 2022: 313-336 - [i9]K. R. Jayaram, Vinod Muthusamy, Gegi Thomas, Ashish Verma, Mark Purcell:
Adaptive Aggregation For Federated Learning. CoRR abs/2203.12163 (2022) - [i8]K. R. Jayaram, Ashish Verma, Gegi Thomas, Vinod Muthusamy:
Just-in-Time Aggregation for Federated Learning. CoRR abs/2208.09740 (2022) - 2021
- [c28]Pau-Chen Cheng, Kevin Eykholt, Zhongshu Gu, Hani Jamjoom, K. R. Jayaram, Enriquillo Valdez, Ashish Verma:
Separation of Powers in Federated Learning (Poster Paper). ResilientFL 2021: 16-18 - [i7]Pau-Chen Cheng, Kevin Eykholt, Zhongshu Gu, Hani Jamjoom, K. R. Jayaram, Enriquillo Valdez, Ashish Verma:
Separation of Powers in Federated Learning. CoRR abs/2105.09400 (2021) - 2020
- [c27]K. R. Jayaram, Archit Verma, Ashish Verma, Gegi Thomas, Colin Sutcher-Shepard:
MYSTIKO: Cloud-Mediated, Private, Federated Gradient Descent. CLOUD 2020: 201-210 - [c26]Ashish Verma, Christopher D. Carothers, K. R. Jayaram, Parijat Dube:
Workshop 19: ScaDL Scalable Deep Learning over Parallel and Distributed Infrastructures. IPDPS Workshops 2020: 985-986 - [c25]Vaibhav Saxena, K. R. Jayaram, Saurav Basu, Yogish Sabharwal, Ashish Verma:
Effective Elastic Scaling of Deep Learning Workloads. MASCOTS 2020: 1-8 - [i6]Vaibhav Saxena, K. R. Jayaram, Saurav Basu, Yogish Sabharwal, Ashish Verma:
Effective Elastic Scaling of Deep Learning Workloads. CoRR abs/2006.13878 (2020) - [i5]K. R. Jayaram, Archit Verma, Ashish Verma, Gegi Thomas, Colin Sutcher-Shepard:
MYSTIKO : : Cloud-Mediated, Private, Federated Gradient Descent. CoRR abs/2012.00740 (2020)
2010 – 2019
- 2019
- [c24]K. R. Jayaram, Anshul Gandhi, Hongyi Xin, Shu Tao:
Adaptively Accelerating Map-Reduce/Spark with GPUs: A Case Study. ICAC 2019: 105-114 - [c23]K. R. Jayaram, Vinod Muthusamy, Parijat Dube, Vatche Ishakian, Chen Wang, Benjamin Herta, Scott Boag, Diana Arroyo, Asser N. Tantawi, Archit Verma, Falk Pollok, Rania Khalaf:
FfDL: A Flexible Multi-tenant Deep Learning Platform. Middleware 2019: 82-95 - [i4]K. R. Jayaram:
Elastic Remote Methods. CoRR abs/1909.03346 (2019) - [i3]K. R. Jayaram, Vinod Muthusamy, Parijat Dube, Vatche Ishakian, Chen Wang, Benjamin Herta, Scott Boag, Diana Arroyo, Asser N. Tantawi, Archit Verma, Falk Pollok, Rania Khalaf:
FfDL : A Flexible Multi-tenant Deep Learning Platform. CoRR abs/1909.06526 (2019) - 2018
- [c22]Scott Boag, Parijat Dube, Kaoutar El Maghraoui, Benjamin Herta, Waldemar Hummer, K. R. Jayaram, Rania Khalaf, Vinod Muthusamy, Michael H. Kalantar, Archit Verma:
Dependability in a Multi-tenant Multi-framework Deep Learning as-a-Service Platform. DSN Workshops 2018: 43-46 - [i2]Scott Boag, Parijat Dube, Kaoutar El Maghraoui, Benjamin Herta, Waldemar Hummer, K. R. Jayaram, Rania Khalaf, Vinod Muthusamy, Michael H. Kalantar, Archit Verma:
Dependability in a Multi-tenant Multi-framework Deep Learning as-a-Service Platform. CoRR abs/1805.06801 (2018) - 2017
- [j5]Bishwaranjan Bhattacharjee, Scott Boag, Chandani Doshi, Parijat Dube, Ben Herta, Vatche Ishakian, K. R. Jayaram, Rania Khalaf, Avesh Krishna, Yu Bo Li, Vinod Muthusamy, Ruchir Puri, Yufei Ren, Florian Rosenberg, Seetharami R. Seelam, Yi Wang, Jian Ming Zhang, Li Zhang:
IBM Deep Learning Service. IBM J. Res. Dev. 61(4-5): 10:1-10:11 (2017) - [c21]Antorweep Chakravorty, Chunming Rong, K. R. Jayaram, Shu Tao:
Scalable, Efficient Anonymization with INCOGNITO - Framework & Algorithm. BigData Congress 2017: 39-48 - [c20]Michael Le, K. R. Jayaram, Yaron Weinsberg, Daniel J. Dean, Shu Tao:
Agile Composition of Compliant Data Analytics Platforms. IC2E 2017: 51-58 - [p2]K. R. Jayaram, Aleksandar Milenkoski, Samuel Kounev:
Software Architectures for Self-protection in IaaS Clouds. Self-Aware Computing Systems 2017: 611-631 - [p1]Aleksandar Milenkoski, K. R. Jayaram, Samuel Kounev:
Benchmarking Intrusion Detection Systems with Adaptive Provisioning of Virtualized Resources. Self-Aware Computing Systems 2017: 633-657 - [e2]K. R. Jayaram, Anshul Gandhi, Bettina Kemme, Peter R. Pietzuch:
Proceedings of the 18th ACM/IFIP/USENIX Middleware Conference, Las Vegas, NV, USA, December 11 - 15, 2017. ACM 2017, ISBN 978-1-4503-4720-4 [contents] - [i1]Bishwaranjan Bhattacharjee, Scott Boag, Chandani Doshi, Parijat Dube, Ben Herta, Vatche Ishakian, K. R. Jayaram, Rania Khalaf, Avesh Krishna, Yu Bo Li, Vinod Muthusamy, Ruchir Puri, Yufei Ren, Florian Rosenberg, Seetharami R. Seelam, Yandong Wang, Jian Ming Zhang, Li Zhang:
IBM Deep Learning Service. CoRR abs/1709.05871 (2017) - 2016
- [c19]K. R. Jayaram:
Exploiting Causality to Engineer Elastic Distributed Software. ICDCS 2016: 232-241 - [c18]Aleksandar Milenkoski, K. R. Jayaram, Nuno Antunes, Marco Vieira, Samuel Kounev:
Quantifying the Attack Detection Accuracy of Intrusion Detection Systems in Virtualized Environments. ISSRE 2016: 276-286 - 2015
- [j4]K. R. Jayaram, Weihang Wang, Patrick Eugster:
Subscription Normalization for Effective Content-Based Messaging. IEEE Trans. Parallel Distributed Syst. 26(11): 3184-3193 (2015) - [c17]K. R. Jayaram:
Towards Explicitly Elastic Programming Frameworks. ICSE (2) 2015: 619-622 - [e1]K. R. Jayaram, Michael A. Kozuch:
Proceedings of the Industrial Track of the 16th International Middleware Conference, Middleware Industry 2015, Vancouver, BC, Canada, December 7-11, 2015. ACM 2015, ISBN 978-1-4503-3727-4 [contents] - 2014
- [j3]Gregory Aaron Wilkin, Patrick Eugster, K. R. Jayaram:
Decentralized Fault-Tolerant Event Correlation. ACM Trans. Internet Techn. 14(1): 5:1-5:27 (2014) - [c16]K. R. Jayaram, David Safford, Upendra Sharma, Vijay K. Naik, Dimitrios E. Pendarakis, Shu Tao:
Trustworthy geographically fenced hybrid clouds. Middleware 2014: 37-48 - [c15]William Culhane, K. R. Jayaram, Patrick Eugster:
Fast, expressive top-k matching. Middleware 2014: 73-84 - 2013
- [j2]K. R. Jayaram, Patrick Eugster, Chamikara Jayalath:
Parametric Content-Based Publish/Subscribe. ACM Trans. Comput. Syst. 31(2): 4 (2013) - [c14]K. R. Jayaram:
Elastic Remote Methods. Middleware 2013: 143-162 - [c13]Michael Mihn-Jong Lee, Indrajit Roy, Alvin AuYoung, Vanish Talwar, K. R. Jayaram, Yuanyuan Zhou:
Views and Transactional Storage for Large Graphs. Middleware 2013: 287-306 - 2012
- [j1]Adrian Holzer, Lukasz Ziarek, K. R. Jayaram, Patrick Eugster:
Abstracting Context in Event-Based Software. LNCS Trans. Aspect Oriented Softw. Dev. 9: 123-167 (2012) - [c12]William Culhane, K. R. Jayaram, Patrick Eugster:
Brief Announcement: Weighted Partial Message Matching for Implicit Multicast Systems. DISC 2012: 447-448 - 2011
- [c11]Adrian Holzer, Lukasz Ziarek, K. R. Jayaram, Patrick Eugster:
Putting events in context: aspects for event-based distributed programming. AOSD 2011: 241-252 - [c10]K. R. Jayaram, Patrick Eugster:
Program analysis for event-based distributed systems. DEBS 2011: 113-124 - [c9]K. R. Jayaram, Patrick Eugster:
Split and Subsume: Subscription Normalization for Effective Content-Based Messaging. ICDCS 2011: 824-835 - [c8]Gregory Aaron Wilkin, K. R. Jayaram, Patrick Eugster, Ankur Khetrapal:
FAIDECS: Fair Decentralized Event Correlation. Middleware 2011: 228-248 - 2010
- [c7]K. R. Jayaram, Patrick Th. Eugster:
Scalable Efficient Composite Event Detection. COORDINATION 2010: 168-182 - [c6]K. R. Jayaram, Chamikara Jayalath, Patrick Eugster:
Parametric Subscriptions for Content-Based Publish/Subscribe Networks. Middleware 2010: 128-147
2000 – 2009
- 2009
- [c5]K. R. Jayaram, Patrick Eugster:
Context-oriented programming with EventJava. COP@ECOOP 2009: 9:1-9:6 - [c4]Patrick Th. Eugster, K. R. Jayaram:
EventJava: An Extension of Java for Event Correlation. ECOOP 2009: 570-594 - 2008
- [c3]K. R. Jayaram, Aditya P. Mathur:
On the Adequacy of Statecharts as a Source of Tests for Cryptographic Protocols. COMPSAC 2008: 937-942 - [c2]Christopher Line, K. R. Jayaram, Patrick Eugster:
Lazy argument passing in Java RMI. PPPJ 2008: 127-136 - 2006
- [c1]K. R. Jayaram:
Identifying andTesting for Insecure Paths in Cryptographic Protocol Implementations. COMPSAC (2) 2006: 368-369
Coauthor Index
aka: Patrick Th. Eugster
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