Publications

Siavash Ghiasvand. uPAD: Unsupervised Privacy-Aware Anomaly Detection in High Performance Computing Systems:. Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods, 852--859, SCITEPRESS - Science and Technology Publications, Prague, Czech Republic, 2019. [PUMA: myOwn] URL

Siavash Ghiasvand, and Florina M Ciorba. Automatic Classification of System Logs. International Supercomputing Conference, Frankfurt, Germany, June 2018. [PUMA: myOwn]

Siavash Ghiasvand, and Florina M. Ciorba. Assessing Data Usefulness for Failure Analysis in Anonymized System Logs. Proceedings of the 17th International Symposium on Parallel and Distributed Computing (ISPDC), 164--171, Geneva, Switzerland, June 2018. [PUMA: Data Distributed Encoding, Encryption, High Measurement, Privacy, analysis, anonymization, behavior computing, databases, detection, dissertation encoding, failure high myOwn performance privacy, usefulness,]

Siavash Ghiasvand, Wolfgang E Nagel, and Florina M Ciorba. Toward Resilience in HPC: A Prototype to Analyze and Predict System Behavior. International Supercomputing Conference (ISC), Frankfurt, Germany, June 2016. [PUMA: myOwn]

Tom Richard Vargis, and Siavash Ghiasvand. A Light-weight and Unsupervised Method for Near Real-time Behavioral Analysis using Operational Data Measurement. The International Conference for High Performance Computing, Networking, Storage, and Analysis, Dallas, Texas, USA, January 2022. [PUMA: Cluster Computer Computing, Distributed, Learning Machine Parallel, Science and myOwn] URL

Tom Richard Vargis, and Siavash Ghiasvand. Content-Aware Depth-Adaptive Image Restoration. Proceedings of the 29th International Conference on Automation and Computing, Sunderland, UK, January 2024. [PUMA: Computer Learning, Machine Pattern Recognition, Science Vision and myOwn] URL

Tom Richard Vargis, and Siavash Ghiasvand. Assessing Anonymized System Logs Usefulness for Behavioral Analysis in RNN Models. Proceedings of the International Workshop on Data-driven Resilience Research, (3376)arXiv, Leipzig, Germany, December 2022. [PUMA: myOwn] URL

Lincoln Sherpa, Sima Attar Khorasani, Rajasekar Sankar, Ralph Müller-Pfefferkorn, and Siavash Ghiasvand. KEENsight: Cloud based Collaborative Environment for Streamlining Machine Learning Development. The Fifteenth International Conference on Information, Intelligence, Systems and Applications, Crete, Greece, June 2024. [PUMA: myOwn]

Christopher Schröder, and Gerhard Heyer. Self-Training for Sample-Efficient Active Learning for Text Classification with Pre-Trained Language Models. In Yaser Al-Onaizan, Mohit Bansal, and Yun-Nung Chen (Eds.), Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 11987--12004, Association for Computational Linguistics, Miami, Florida, USA, November 2024. [PUMA: active_learning llms myown self_training text_classification] URL

Yuhao Liu, Salim Ullah, and Akash Kumar. BitSys: Bitwise Systolic Array Architecture for Multi-precision Quantized Hardware Accelerators. 2024 IEEE 32nd Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), 220-220, 2024. [PUMA: hardware multiplier myown quantization systolic]

Yuhao Liu, Shubham Rai, Salim Ullah, and Akash Kumar. High-Flexibility Designs of Quantized Runtime Reconfigurable Multi-Precision Multipliers. IEEE Embedded Systems Letters, (15)4:194-197, 2023. [PUMA: FPGA Hardware Multi-precision Multiplier Quantization myown]

Yuhao Liu, Shubham Rai, Salim Ullah, and Akash Kumar. NetPU-M: a Generic Reconfigurable Neural Network Accelerator Architecture for MLPs. 2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 85-92, 2023. [PUMA: Accelerator FPGA Quantization Reconfiguration myown]