K. R. Jayaram

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 27

Top Topics

Intrusion Detection System

Classification Models

Top Venues

WOSC@Middleware

Publications

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)
Rahul Atul Bhope, K. R. Jayaram, Nalini Venkatasubramanian, Ashish Verma, Gegi Thomas
FLIPS: Federated Learning using Intelligent Participant Selection. CoRR (2023)
Rahul Atul Bhope, K. R. Jayaram, Nalini Venkatasubramanian, Ashish Verma, Gegi Thomas
FLIPS: Federated Learning using Intelligent Participant Selection. Middleware (2023)
Aurora González-Vidal, Alexander Isenko, K. R. Jayaram
On Serving Image Classification Models. WOSC@Middleware (2023)
K. R. Jayaram, Vinod Muthusamy, Gegi Thomas, Ashish Verma, Mark Purcell
Adaptive Aggregation For Federated Learning. Big Data (2022)
K. R. Jayaram, Vinod Muthusamy, Gegi Thomas, Ashish Verma, Mark Purcell
Adaptive Aggregation For Federated Learning. CoRR (2022)
K. R. Jayaram, Ashish Verma, Gegi Thomas, Vinod Muthusamy
Just-in-Time Aggregation for Federated Learning. MASCOTS (2022)
K. R. Jayaram, Ashish Verma, Gegi Thomas, Vinod Muthusamy
Just-in-Time Aggregation for Federated Learning. CoRR (2022)
Pau-Chen Cheng, Kevin Eykholt, Zhongshu Gu, Hani Jamjoom, K. R. Jayaram, Enriquillo Valdez, Ashish Verma
Separation of Powers in Federated Learning. CoRR (2021)
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)
Ashish Verma, Christopher D. Carothers, K. R. Jayaram, Parijat Dube
Workshop 19: ScaDL Scalable Deep Learning over Parallel and Distributed Infrastructures. IPDPS Workshops (2020)
K. R. Jayaram, Archit Verma, Ashish Verma, Gegi Thomas, Colin Sutcher-Shepard
MYSTIKO: Cloud-Mediated, Private, Federated Gradient Descent. CLOUD (2020)
K. R. Jayaram, Archit Verma, Ashish Verma, Gegi Thomas, Colin Sutcher-Shepard
MYSTIKO : : Cloud-Mediated, Private, Federated Gradient Descent. CoRR (2020)
Vaibhav Saxena, K. R. Jayaram, Saurav Basu, Yogish Sabharwal, Ashish Verma
Effective Elastic Scaling of Deep Learning Workloads. CoRR (2020)
Vaibhav Saxena, K. R. Jayaram, Saurav Basu, Yogish Sabharwal, Ashish Verma
Effective Elastic Scaling of Deep Learning Workloads. MASCOTS (2020)
K. R. Jayaram, Anshul Gandhi, Hongyi Xin, Shu Tao
Adaptively Accelerating Map-Reduce/Spark with GPUs: A Case Study. ICAC (2019)
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 (2019)
K. R. Jayaram
Elastic Remote Methods. CoRR (2019)
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)
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 (2018)
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)
Antorweep Chakravorty, Chunming Rong, K. R. Jayaram, Shu Tao
Scalable, Efficient Anonymization with INCOGNITO - Framework & Algorithm. BigData Congress (2017)
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 (2017)
Michael Le, K. R. Jayaram, Yaron Weinsberg, Daniel J. Dean, Shu Tao
Agile Composition of Compliant Data Analytics Platforms. IC2E (2017)
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) (2017)
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)
K. R. Jayaram
Exploiting Causality to Engineer Elastic Distributed Software. ICDCS (2016)
K. R. Jayaram, Weihang Wang, Patrick Eugster
Subscription Normalization for Effective Content-Based Messaging. IEEE Trans. Parallel Distributed Syst. 26 (11) (2015)
K. R. Jayaram
Towards Explicitly Elastic Programming Frameworks. ICSE (2) (2015)
K. R. Jayaram, David Safford, Upendra Sharma, Vijay K. Naik, Dimitrios E. Pendarakis, Shu Tao
Trustworthy geographically fenced hybrid clouds. Middleware (2014)
William Culhane, K. R. Jayaram, Patrick Eugster
matching. Middleware (2014)
Gregory Aaron Wilkin, Patrick Eugster, K. R. Jayaram
Decentralized Fault-Tolerant Event Correlation. ACM Trans. Internet Techn. 14 (1) (2014)
Michael Mihn-Jong Lee, Indrajit Roy, Alvin AuYoung, Vanish Talwar, K. R. Jayaram, Yuanyuan Zhou
Views and Transactional Storage for Large Graphs. Middleware (2013)
K. R. Jayaram
Elastic Remote Methods. Middleware (2013)
K. R. Jayaram, Patrick Eugster, Chamikara Jayalath
Parametric Content-Based Publish/Subscribe. ACM Trans. Comput. Syst. 31 (2) (2013)
William Culhane, K. R. Jayaram, Patrick Eugster
Brief Announcement: Weighted Partial Message Matching for Implicit Multicast Systems. DISC (2012)
Adrian Holzer, Lukasz Ziarek, K. R. Jayaram, Patrick Eugster
Abstracting Context in Event-Based Software. LNCS Trans. Aspect Oriented Softw. Dev. 9 (2012)
K. R. Jayaram, Patrick Eugster
Program analysis for event-based distributed systems. DEBS (2011)
Adrian Holzer, Lukasz Ziarek, K. R. Jayaram, Patrick Eugster
Putting events in context: aspects for event-based distributed programming. AOSD (2011)
Gregory Aaron Wilkin, K. R. Jayaram, Patrick Eugster, Ankur Khetrapal
FAIDECS: Fair Decentralized Event Correlation. Middleware (2011)
K. R. Jayaram, Patrick Eugster
Split and Subsume: Subscription Normalization for Effective Content-Based Messaging. ICDCS (2011)
K. R. Jayaram, Patrick Th. Eugster
Scalable Efficient Composite Event Detection. COORDINATION (2010)
K. R. Jayaram, Chamikara Jayalath, Patrick Eugster
Parametric Subscriptions for Content-Based Publish/Subscribe Networks. Middleware (2010)
K. R. Jayaram, Patrick Eugster
Context-oriented programming with EventJava. COP@ECOOP (2009)
Patrick Th. Eugster, K. R. Jayaram
EventJava: An Extension of Java for Event Correlation. ECOOP (2009)
Christopher Line, K. R. Jayaram, Patrick Eugster
Lazy argument passing in Java RMI. PPPJ (2008)
K. R. Jayaram, Aditya P. Mathur
On the Adequacy of Statecharts as a Source of Tests for Cryptographic Protocols. COMPSAC (2008)
K. R. Jayaram
Identifying andTesting for Insecure Paths in Cryptographic Protocol Implementations. COMPSAC (2) (2006)