A swarm pattern transformation method based on macroscopic parameter operations. - Blesson Varghese; Gerard T. McKee (ROBIO, 2008)

Can Space Applications Benefit from Intelligent Agents? - Blesson Varghese; Gerard T. McKee (Autonomics, 2009)

Modeling and Simulating a Mathematical Tool for Multi-robot Pattern Transformation. - Blesson Varghese; Gerard T. McKee (ICCMS, 2009)

Autonomous Execution of Tasks by Swarm Carrier Agents in Swarm-Array Computing. - Blesson Varghese; Gerard T. McKee (IDC, 2009)

Investigating feasible tools for swarm pattern transformation. - Blesson Varghese; Gerard T. McKee (ROBOCOMM, 2009)

Swarm pattern transformation methodologies. - Blesson Varghese; Gerard T. McKee (SIS, 2009)

A review and implementation of swarm pattern formation and transformation models. - Blesson Varghese; Gerard T. McKee (Int. J. Intell. Comput. Cybern., 2009)

Intelligent Agents for Fault Tolerance: From Multi-agent Simulation to Cluster-Based Implementation. - Blesson Varghese; Gerard T. McKee; Vassil Alexandrov 001 (AINA Workshops, 2010)

A Cluster-Based Implementation of a Fault Tolerant Parallel Reduction Algorithm Using Swarm-Array Computing. - Blesson Varghese; Gerard T. McKee; Vassil Alexandrov 001 (ICAS, 2010)

An MPI-based implementation of intelligent agents on clusters. - Blesson Varghese; Gerard T. McKee; Vassil Alexandrov 001 (SpringSim, 2010)

Implementing intelligent cores using processor virtualization for fault tolerance. - Blesson Varghese; Gerard T. McKee; Vassil Alexandrov 001 (ICCS, 2010)

A mathematical model, implementation and study of a swarm system. - Blesson Varghese; Gerard T. McKee (Robotics Auton. Syst., 2010)

Exploring Carrier Agents in Swarm-Array Computing. - Blesson Varghese; Gerard T. McKee (Scalable Comput. Pract. Exp., 2010)

Can Agent Intelligence be Used to Achieve Fault Tolerant Parallel Computing Systems? - Blesson Varghese; Gerard T. McKee; Vassil Alexandrov 001 (Parallel Process. Lett., 2011)

Swarm-array computing : a swarm robotics inspired approach to achieve automated fault tolerance in high-performance computing systems. - Blesson Varghese (2011)

Rapid Post-event Catastrophe Modelling and Visualization. - Eric Mason; Andrew Rau-Chaplin; Kunal Shridhar; Blesson Varghese; Naman Varshney (DEXA Workshops, 2012)

A Platform for Parallel R-based Analytics on Cloud Infrastructure. - Ishan Patel; Andrew Rau-Chaplin; Blesson Varghese (ICPP Workshops, 2012)

Parallel Simulations for Analysing Portfolios of Catastrophic Event Risk. - Aman Kumar Bahl; Oliver Baltzer; Andrew Rau-Chaplin; Blesson Varghese (SC Companion, 2012)

Data Challenges in High-Performance Risk Analytics. - Blesson Varghese; Andrew Rau-Chaplin (SC Companion, 2012)

Robotic Ecologies for Deep Space Outposts. - Gerard T. McKee; Blesson Varghese (SyRoCo, 2012)

The royal birth of 2013: Analysing and visualising public sentiment in the UK using Twitter. - Vu Dung Nguyen; Blesson Varghese; Adam Barker (IEEE BigData, 2013)

QuPARA: Query-driven large-scale portfolio aggregate risk analysis on MapReduce. - Andrew Rau-Chaplin; Blesson Varghese; Duane Wilson; Zhimin Yao; Norbert Zeh (IEEE BigData, 2013)

Risk Analytics for Estimating and Validating Magnitude of Earthquake Losses. - Anthony Astoul; Christopher Filliter; Andrew Rau-Chaplin; Kunal Shridhar; Blesson Varghese; Naman Varshney (DEXA Workshops, 2013)

High performance risk aggregation: addressing the data processing challenge the hadoop mapreduce way. - Zhimin Yao; Blesson Varghese; Andrew Rau-Chaplin (ScienceCloud@HPDC, 2013)

A MapReduce Framework for Analysing Portfolios of Catastrophic Risk with Secondary Uncertainty. - Andrew Rau-Chaplin; Blesson Varghese; Zhimin Yao (ICCS, 2013)

Achieving Speedup in Aggregate Risk Analysis Using Multiple GPUs. - Aman K. Bahl; Oliver Baltzer; Andrew Rau-Chaplin; Blesson Varghese; Aaron Whiteway (ICPP, 2013)

Accounting for secondary uncertainty: efficient computation of portfolio risk measures on multi and many core architectures. - Blesson Varghese; Andrew Rau-Chaplin (WHPCF@SC, 2013)

Developing and Testing the Automated Post-Event Earthquake Loss Estimation and Visualisation (APE-ELEV) Technique. - Anthony Astoul; Christopher Filliter; Eric Mason; Andrew Rau-Chaplin; Kunal Shridhar; Blesson Varghese; Naman Varshney (CoRR, 2013)

Are Clouds Ready to Accelerate Ad Hoc Financial Simulations? - Blesson Varghese; Adam Barker (BDC, 2014)

BigExcel: A web-based framework for exploring big data in social sciences. - Muhammed Asif Saleem; Blesson Varghese; Adam Barker (IEEE BigData, 2014)

Optimal Deployment of Geographically Distributed Workflow Engines on the Cloud. - Long Thai; Adam Barker; Blesson Varghese; Ozgur Akgun; Ian Miguel (CloudCom, 2014)

Executing Bag of Distributed Tasks on the Cloud: Investigating the Trade-Offs between Performance and Cost. - Long Thai; Blesson Varghese; Adam Barker (CloudCom, 2014)

Cloud Benchmarking for Performance. - Blesson Varghese; Ozgur Akgun; Ian Miguel; Long Thai; Adam Barker (CloudCom, 2014)

Academic Cloud Computing Research: Five Pitfalls and Five Opportunities. - Adam Barker; Blesson Varghese; Jonathan Stuart Ward; Ian Sommerville (HotCloud, 2014)

Automating fault tolerance in high-performance computational biological jobs using multi-agent approaches. - Blesson Varghese; Gerard T. McKee; Vassil Alexandrov 001 (Comput. Biol. Medicine, 2014)

Cloud Services Brokerage: A Survey and Research Roadmap. - Adam Barker; Blesson Varghese; Long Thai (CLOUD, 2015)

Budget Constrained Execution of Multiple Bag-of-Tasks Applications on the Cloud. - Long Thai; Blesson Varghese; Adam Barker (CLOUD, 2015)

Executing Bag of Distributed Tasks on Virtually Unlimited Cloud Resources. - Long Thai; Blesson Varghese; Adam Barker (CLOSER, 2015)

Acceleration-as-a-Service: Exploiting Virtualised GPUs for a Financial Application. - Blesson Varghese; Javier Prades; Carlos Reaño; Federico Silla (e-Science, 2015)

Cloud-based E-Infrastructure for Scheduling Astronomical Observations. - James Wetter; Ozgur Akgun; Adam Barker; Martin Dominik; Ian Miguel; Blesson Varghese (e-Science, 2015)

Task Scheduling on the Cloud with Hard Constraints. - Long Thai; Blesson Varghese; Adam Barker (SERVICES, 2015)

The hardware accelerator debate: A financial risk case study using many-core computing. - Blesson Varghese (Comput. Electr. Eng., 2015)

The GPU vs Phi Debate: Risk Analytics Using Many-Core Computing. - Blesson Varghese (CoRR, 2015)

RBioCloud: A Light-Weight Framework for Bioconductor and R-based Jobs on the Cloud. - Blesson Varghese; Ishan Patel; Adam Barker (IEEE ACM Trans. Comput. Biol. Bioinform., 2015)

DocLite: A Docker-Based Lightweight Cloud Benchmarking Tool. - Blesson Varghese; Lawan Thamsuhang Subba; Long Thai; Adam Barker (CCGrid, 2016)

Algorithms for Optimising Heterogeneous Cloud Virtual Machine Clusters. - Long Thai; Blesson Varghese; Adam Barker (CloudCom, 2016)

A machine learning analysis of Twitter sentiment to the Sandy Hook shootings. - Nan Wang 009; Blesson Varghese; Peter D. Donnelly (eScience, 2016)

Minimising the Execution of Unknown Bag-of-Task Jobs with Deadlines on the Cloud. - Long Thai; Blesson Varghese; Adam Barker (DIDC@HPDC, 2016)

Container-Based Cloud Virtual Machine Benchmarking. - Blesson Varghese; Lawan Thamsuhang Subba; Long Thai; Adam Barker (IC2E, 2016)

Challenges and Opportunities in Edge Computing. - Blesson Varghese; Nan Wang 009; Sakil Barbhuiya; Peter Kilpatrick; Dimitrios S. Nikolopoulos (SmartCloud, 2016)

Computing probable maximum loss in catastrophe reinsurance portfolios on multi-core and many-core architectures. - Neil Burke; Andrew Rau-Chaplin; Blesson Varghese (Concurr. Comput. Pract. Exp., 2016)

Accelerating R-based analytics on the cloud. - Ishan Patel; Andrew Rau-Chaplin; Blesson Varghese (Concurr. Comput. Pract. Exp., 2016)

Plug and play bench: Simplifying big data benchmarking using containers. - Sheriffo Ceesay; Adam Barker; Blesson Varghese (IEEE BigData, 2017)

Power Modelling for Heterogeneous Cloud-Edge Data Centers. - Kai Chen; Blesson Varghese; Peter Kilpatrick; Dimitrios S. Nikolopoulos (PARCO, 2017)

Edge-as-a-Service: Towards Distributed Cloud Architectures. - Blesson Varghese; Nan Wang 009; Jianyu Li; Dimitrios S. Nikolopoulos (PARCO, 2017)

Feasibility of Fog Computing. - Blesson Varghese; Nan Wang 009; Dimitrios S. Nikolopoulos; Rajkumar Buyya (CoRR, 2017)

Multi-tenant virtual GPUs for optimising performance of a financial risk application. - Javier Prades; Blesson Varghese; Carlos Reaño; Federico Silla (J. Parallel Distributed Comput., 2017)

Accelerator Virtualization in Fog Computing: Moving from the Cloud to the Edge. - Blesson Varghese; Carlos Reaño; Federico Silla (IEEE Cloud Comput., 2018)

Realizing Edge Marketplaces: Challenges and Opportunities. - Blesson Varghese; Massimo Villari; Omer F. Rana; Philip James 002; Tejal Shah; Maria Fazio; Rajiv Ranjan 001 (IEEE Cloud Comput., 2018)

Addressing the Challenges in Federating Edge Resources. - Ahmet Cihat Baktir; Cagatay Sonmez; Cem Ersoy; Atay Ozgovde; Blesson Varghese (CoRR, 2018)

Resource Management in Fog/Edge Computing: A Survey. - Cheol-Ho Hong; Blesson Varghese (CoRR, 2018)

A survey and taxonomy of resource optimisation for executing bag-of-task applications on public clouds. - Long Thai; Blesson Varghese; Adam Barker (Future Gener. Comput. Syst., 2018)

Next generation cloud computing: New trends and research directions. - Blesson Varghese; Rajkumar Buyya (Future Gener. Comput. Syst., 2018)

Intra-Node Memory Safe GPU Co-Scheduling. - Carlos Reaño; Federico Silla; Dimitrios S. Nikolopoulos; Blesson Varghese (IEEE Trans. Parallel Distributed Syst., 2018)

Addressing the Challenges in Federating Edge Resources. - Ahmet Cihat Baktir; Cagatay Sonmez; Cem Ersoy; Atay Ozgovde; Blesson Varghese (Fog and Edge Computing, 2019)

Research challenges in query processing and data analytics on the edge. - Blesson Varghese; Suprio Ray; Bhavesh N. Gohil; Sergio Vega (CASCON, 2019)

DeFog: fog computing benchmarks. - Jonathan McChesney; Nan Wang 009; Ashish Tanwer; Eyal de Lara; Blesson Varghese (SEC, 2019)

Performance Estimation of Container-Based Cloud-to-Fog Offloading. - Ayesha Abdul Majeed; Peter Kilpatrick; Ivor T. A. Spence; Blesson Varghese (UCC Companion, 2019)

Cloud Futurology. - Blesson Varghese; Philipp Leitner 001; Suprio Ray; Kyle Chard; Adam Barker; Yehia Elkhatib; Herry Herry; Cheol-Ho Hong; Jeremy Singer; Fung Po Tso 001; Eiko Yoneki; Mohamed Faten Zhani (Computer, 2019)

A Manifesto for Future Generation Cloud Computing: Research Directions for the Next Decade. - Rajkumar Buyya; Satish Narayana Srirama; Giuliano Casale; Rodrigo N. Calheiros; Yogesh Simmhan; Blesson Varghese; Erol Gelenbe; Bahman Javadi; Luis Miguel Vaquero; Marco A. S. Netto; Adel Nadjaran Toosi; Maria Alejandra Rodriguez; et al. (ACM Comput. Surv., 2019)

Resource Management in Fog/Edge Computing: A Survey on Architectures, Infrastructure, and Algorithms. - Cheol-Ho Hong; Blesson Varghese (ACM Comput. Surv., 2019)

Cloud Benchmarking for Maximising Performance of Scientific Applications. - Blesson Varghese; Ozgur Akgun; Ian Miguel; Long Thai; Adam Barker (IEEE Trans. Cloud Comput., 2019)

Cross Architectural Power Modelling. - Kai Chen; Peter Kilpatrick; Dimitrios S. Nikolopoulos; Blesson Varghese (CCGRID, 2020)

Priority-based Fair Scheduling in Edge Computing. - Arkadiusz Madej; Nan Wang 009; Nikolaos Athanasopoulos; Rajiv Ranjan 001; Blesson Varghese (ICFEC, 2020)

Modelling Fog Offloading Performance. - Ayesha Abdul Majeed; Peter Kilpatrick; Ivor T. A. Spence; Blesson Varghese (ICFEC, 2020)

Scission: Performance-driven and Context-aware Cloud-Edge Distribution of Deep Neural Networks. - Luke Lockhart; Paul Harvey 002; Pierre Imai; Peter Willis 001; Blesson Varghese (UCC, 2020)

WattsApp: Power-Aware Container Scheduling. - Hemant Kumar Mehta; Paul Harvey 002; Omer F. Rana; Rajkumar Buyya; Blesson Varghese (UCC, 2020)

A Survey on Edge Benchmarking. - Blesson Varghese; Nan Wang 009; David Bermbach; Cheol-Ho Hong; Eyal de Lara; Weisong Shi; Christopher Stewart (CoRR, 2020)

Scission: Context-aware and Performance-driven Edge-based Distributed Deep Neural Networks. - Luke Lockhart; Paul Harvey 002; Pierre Imai; Peter Willis 001; Blesson Varghese (CoRR, 2020)

DYVERSE: DYnamic VERtical Scaling in multi-tenant Edge environments. - Nan Wang 009; Michail Matthaiou; Dimitrios S. Nikolopoulos; Blesson Varghese (Future Gener. Comput. Syst., 2020)

IoTSim-SDWAN: A simulation framework for interconnecting distributed datacenters over Software-Defined Wide Area Network (SD-WAN). - Khaled Alwasel; Devki Nandan Jha; Eduardo Hernández; Deepak Puthal; Mutaz Barika; Blesson Varghese; Saurabh Kumar Garg 001; Philip James 002; Albert Y. Zomaya; Graham Morgan; Rajiv Ranjan 001 (J. Parallel Distributed Comput., 2020)

New generation cloud computing. - Blesson Varghese; Marco A. S. Netto; Ignacio Martín Llorente; Rajkumar Buyya (Softw. Pract. Exp., 2020)

ENORM: A Framework For Edge NOde Resource Management. - Nan Wang 009; Blesson Varghese; Michail Matthaiou; Dimitrios S. Nikolopoulos (IEEE Trans. Serv. Comput., 2020)

The Case for Adaptive Deep Neural Networks in Edge Computing. - Francis McNamee; Schahram Dustdar; Peter Kilpatrick; Weisong Shi; Ivor T. A. Spence; Blesson Varghese (CLOUD, 2021)

NEUKONFIG: Reducing Edge Service Downtime When Repartitioning DNNs. - Ayesha Abdul Majeed; Peter Kilpatrick; Ivor T. A. Spence; Blesson Varghese (IC2E, 2021)

AVEC: Accelerator Virtualization in Cloud-Edge Computing for Deep Learning Libraries. - Jason Kennedy; Blesson Varghese; Carlos Reaño (ICFEC, 2021)

TOD: Transprecise Object Detection to Maximise Real-Time Accuracy on the Edge. - JunKyu Lee; Blesson Varghese; Roger F. Woods; Hans Vandierendonck (ICFEC, 2021)

QUDOS: quorum-based cloud-edge distributed DNNs for security enhanced industry 4.0. - Kevin Wallis; Christoph Reich; Blesson Varghese; Christian Schindelhauer (UCC, 2021)

ScissionLite: Accelerating Distributed Deep Neural Networks Using Transfer Layer. - Hyunho Ahn; Munkyu Lee; Cheol-Ho Hong; Blesson Varghese (CoRR, 2021)

FedFly: Towards Migration in Edge-based Distributed Federated Learning. - Rehmat Ullah 001; Di Wu 065; Paul Harvey 002; Peter Kilpatrick; Ivor T. A. Spence; Blesson Varghese (CoRR, 2021)

Roadmap for Edge AI: A Dagstuhl Perspective. - Aaron Yi Ding; Ella Peltonen; Tobias Meuser; Atakan Aral; Christian Becker 001; Schahram Dustdar; Thomas Hiessl; Dieter Kranzlmüller; Madhusanka Liyanage; Setareh Magshudi; Nitinder Mohan; Jörg Ott; et al. (CoRR, 2021)

Toward Sustainable Serverless Computing. - Panos Patros; Josef Spillner; Alessandro V. Papadopoulos; Blesson Varghese; Omer F. Rana; Schahram Dustdar (IEEE Internet Comput., 2021)

Revisiting the Arguments for Edge Computing Research. - Blesson Varghese; Eyal de Lara; Aaron Yi Ding; Cheol-Ho Hong; Flavio Bonomi; Schahram Dustdar; Paul Harvey 002; Peter Hewkin; Weisong Shi; Mark Thiele; Peter Willis 001 (IEEE Internet Comput., 2021)

Editorial. - Carlos Reaño; Federico Silla; Blesson Varghese (J. Parallel Distributed Comput., 2021)

CONTINUER: Maintaining Distributed DNN Services During Edge Failures. - Ayesha Abdul Majeed; Peter Kilpatrick; Ivor T. A. Spence; Blesson Varghese (EDGE, 2022)

Measuring Torque Production with a Robotic Exoskeleton during Cervical Transcutaneous Spinal Stimulation. - Erin E. Mahan; Nathan Dunkelberger; Jeonghoon Oh; Madison Simmons; Blesson Varghese; Dimitry Sayenko; Marcia K. O'Malley (ICORR, 2022)

FedComm: Understanding Communication Protocols for Edge-based Federated Learning. - Gary Cleland; Di Wu 065; Rehmat Ullah 001; Blesson Varghese (UCC, 2022)

Roadmap for edge AI: a Dagstuhl perspective. - Aaron Yi Ding; Ella Peltonen; Tobias Meuser; Atakan Aral; Christian Becker 001; Schahram Dustdar; Thomas Hiessl; Dieter Kranzlmüller; Madhusanka Liyanage; Setareh Maghsudi; Nitinder Mohan; Jörg Ott; et al. (Comput. Commun. Rev., 2022)

Abusive Adversaries in 5G and Beyond IoT. - Vishal Sharma 001; Blesson Varghese; John McAllister; Saraju P. Mohanty (IEEE Consumer Electron. Mag., 2022)

FedFly: Toward Migration in Edge-Based Distributed Federated Learning. - Rehmat Ullah 001; Di Wu 065; Paul Harvey 002; Peter Kilpatrick; Ivor T. A. Spence; Blesson Varghese (IEEE Commun. Mag., 2022)

A Survey on Edge Performance Benchmarking. - Blesson Varghese; Nan Wang 009; David Bermbach; Cheol-Ho Hong; Eyal de Lara; Weisong Shi; Christopher Stewart (ACM Comput. Surv., 2022)

IoTPulse: machine learning-based enterprise health information system to predict alcohol addiction in Punjab (India) using IoT and fog computing. - Arwinder Dhillon; Ashima Singh; Harpreet Vohra; Caroline Ellis; Blesson Varghese; Sukhpal Singh Gill (Enterp. Inf. Syst., 2022)

FedAdapt: Adaptive Offloading for IoT Devices in Federated Learning. - Di Wu 065; Rehmat Ullah 001; Paul Harvey 002; Peter Kilpatrick; Ivor T. A. Spence; Blesson Varghese (IEEE Internet Things J., 2022)

Context-aware distribution of fog applications using deep reinforcement learning. - Nan Wang 009; Blesson Varghese (J. Netw. Comput. Appl., 2022)

ROMA: Run-Time Object Detection To Maximize Real-Time Accuracy. - JunKyu Lee; Blesson Varghese; Hans Vandierendonck (WACV, 2023)

PipeLearn: Pipeline Parallelism for Collaborative Machine Learning. - Zihan Zhang; Philip Rodgers; Peter Kilpatrick; Ivor T. A. Spence; Blesson Varghese (CoRR, 2023)

Communication Efficient DNN Partitioning-based Federated Learning. - Di Wu 065; Rehmat Ullah 001; Philip Rodgers; Peter Kilpatrick; Ivor T. A. Spence; Blesson Varghese (CoRR, 2023)

AI-based fog and edge computing: A systematic review, taxonomy and future directions. - Sundas Iftikhar; Sukhpal Singh Gill; Chenghao Song; Minxian Xu; Mohammad Sadegh Aslanpour; Adel Nadjaran Toosi; Junhui Du; Huaming Wu; Shreya Ghosh 002; Deepraj Chowdhury; Muhammed Golec; Mohit Kumar 004; et al. (Internet Things, 2023)

Stochastic Modeling for Intelligent Software-Defined Vehicular Networks: A Survey. - Banoth Ravi; Blesson Varghese; Ilir Murturi; Praveen Kumar Donta; Schahram Dustdar; Chinmaya Kumar Dehury; Satish Narayana Srirama (Comput., 2023)

Multi-Tier GPU Virtualization for Deep Learning in Cloud-Edge Systems. - Jason Kennedy; Vishal Sharma 001; Blesson Varghese; Carlos Reaño (IEEE Trans. Parallel Distributed Syst., 2023)

Rapid Deployment of DNNs for Edge Computing via Structured Pruning at Initialization. - Bailey J. Eccles; Leon Wong; Blesson Varghese (CCGrid, 2024)

NeuroFlux: Memory-Efficient CNN Training Using Adaptive Local Learning. - Dhananjay Saikumar; Blesson Varghese (EuroSys, 2024)

Accelerator virtualization. - Carlos Reaño; Federico Silla; Blesson Varghese (Concurr. Comput. Pract. Exp., 2024)

DRIVE: Dual Gradient-Based Rapid Iterative Pruning. - Dhananjay Saikumar; Blesson Varghese (CoRR, 2024)

Enabling privacy-aware interoperable and quality IoT data sharing with context. - Tek Raj Chhetri; Chinmaya Kumar Dehury; Blesson Varghese; Anna Fensel; Satish Narayana Srirama; Rance J. DeLong (Future Gener. Comput. Syst., 2024)

PiPar: Pipeline parallelism for collaborative machine learning. - Zihan Zhang; Philip Rodgers; Peter Kilpatrick; Ivor T. A. Spence; Blesson Varghese (J. Parallel Distributed Comput., 2024)

DNNShifter: An efficient DNN pruning system for edge computing. - Bailey J. Eccles; Philip Rodgers; Peter Kilpatrick; Ivor T. A. Spence; Blesson Varghese (Future Gener. Comput. Syst., 2024)

EcoFed: Efficient Communication for DNN Partitioning-Based Federated Learning. - Di Wu 065; Rehmat Ullah 001; Philip Rodgers; Peter Kilpatrick; Ivor T. A. Spence; Blesson Varghese (IEEE Trans. Parallel Distributed Syst., 2024)

ScissionLite: Accelerating Distributed Deep Learning With Lightweight Data Compression for IIoT. - Hyunho Ahn; Munkyu Lee; Sihoon Seong; Gap-Joo Na; In-Geol Chun; Blesson Varghese; Cheol-Ho Hong (IEEE Trans. Ind. Informatics, 2024)

Special Issue on Intelligent Architectures and Platforms for Private Edge Cloud Systems. - Sayed Chhattan Shah; Taehong Kim; Blesson Varghese; Zhi Wang (Future Gener. Comput. Syst., 2025)

Signal Collapse in One-Shot Pruning: When Sparse Models Fail to Distinguish Neural Representations. - Dhananjay Saikumar; Blesson Varghese (CoRR, 2025)

EMO: Edge Model Overlays to Scale Model Size in Federated Learning. - Di Wu 065; Weibo He; Wanglei Feng; Zhenyu Wen; Bin Qian 002; Blesson Varghese (CoRR, 2025)

Resource Utilization Optimized Federated Learning. - Zihan Zhang; Leon Wong; Blesson Varghese (CoRR, 2025)

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning. - Zihan Zhang; Leon Wong; Blesson Varghese (CoRR, 2025)

Mosaic: Composite projection pruning for resource-efficient LLMs. - Bailey J. Eccles; Leon Wong; Blesson Varghese (Future Gener. Comput. Syst., 2026)