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Model Assertions for Monitoring and Improving ML Models [article]

Daniel Kang, Deepti Raghavan, Peter Bailis, Matei Zaharia
2020 arXiv   pre-print
We propose a new abstraction, model assertions, that adapts the classical use of program assertions as a way to monitor and improve ML models.  ...  To prevent errors, ML engineering teams monitor and continuously improve these models.  ...  We further acknowledge Kayvon Fatahalian, James Hong, Dan Fu, Will Crichton, Nikos Arechiga, and Sudeep Pillai for their productive discussions on ML applications.  ... 
arXiv:2003.01668v3 fatcat:bh7csm3skfcqzdis334tpz5fye

The ML test score: A rubric for ML production readiness and technical debt reduction

Eric Breck, Shanqing Cai, Eric Nielsen, Michael Salib, D. Sculley
2017 2017 IEEE International Conference on Big Data (Big Data)  
Testing and monitoring are key considerations for ensuring the production-readiness of an ML system, and for reducing technical debt of ML systems.  ...  improve production readiness and pay down ML technical debt.  ...  ACKNOWLEDGMENT We are very grateful to Keith Arner, Gary Holt, Josh Lovejoy, Fernando Pereira, Todd Phillips, Tal Shaked, Todd Underwood, Martin Wicke, Cory Williams, and Martin Zinkevich for many helpful  ... 
doi:10.1109/bigdata.2017.8258038 dblp:conf/bigdataconf/BreckCNSS17 fatcat:qjmoshv3grbgxgj3et7vtdfdu4

Unsolved Problems in ML Safety [article]

Dan Hendrycks and Nicholas Carlini and John Schulman and Jacob Steinhardt
2022 arXiv   pre-print
We present four problems ready for research, namely withstanding hazards ("Robustness"), identifying hazards ("Monitoring"), reducing inherent model hazards ("Alignment"), and reducing systemic hazards  ...  In response to emerging safety challenges in ML, such as those introduced by recent large-scale models, we provide a new roadmap for ML Safety and refine the technical problems that the field needs to  ...  Sculley, Mark Xu, Beth Barnes, Andreas Terzis, Florian Tramèr, Stella Biderman, Leo Gao, Jacob Hilton, and Thomas Dietterich for their feedback.  ... 
arXiv:2109.13916v4 fatcat:5jq5qxxi3nfuvhboaehhekybfi

Towards safety monitoring of ML-based perception tasks of autonomous systems

Raul S. Ferreira
2020 2020 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)  
However, applying an SM for ML components can be complex in terms of detection and reaction.  ...  Thus, aiming at dealing with this challenging task, this work presents a benchmark architecture for testing ML components with SM, and the current work for dealing with specific ML threats.  ...  The author thanks Jérémie Guiochet, Hélène Waeselynck, Mario Trapp, and Harita Joshi for their guidance during this PhD's 1st year.  ... 
doi:10.1109/issrew51248.2020.00052 fatcat:exz2ngbkwfcr3aftndthbbokie

Survey on Machine Learning Algorithms Enhancing the Functional Verification Process

Khaled A. Ismail, Mohamed A. Abd El Ghany
2021 Electronics  
Current research of deploying different (ML) models prove to be promising in areas such as stimulus constraining, test generation, coverage collection and bug detection and localization.  ...  Machine learning (ML) models proved to be valuable for automating major parts of the process, which have typically occupied the bandwidth of engineers; diverting them from adding new coverage metrics to  ...  For the process of generating assertions, presented resources managed to extract effective assertions with the use of ML models, such as DT and RNN, from existing designs and from input natural language  ... 
doi:10.3390/electronics10212688 fatcat:ic2ub7423rcf3exbjatizaoofu

Knowledge-Based Architecture for Recognising Activities of Older People

Mohamed Bennasar, Blaine A. Price, Avelie Stuart, Daniel Gooch, Ciaran McCormick, Vikram Mehta, Linda Clare, Amel Bennaceur, Jessica Cohen, Arosha K. Bandara, Mark Levine, Bashar Nuseibeh
2019 Procedia Computer Science  
Supervised Machine Learning (ML) algorithms are the most commonly used techniques for this application.  ...  Intraand inter-personal variation in performing complex activities is another challenge for an ML-based activity recognition approach.  ...  Acknowledgements This research was part funded by UK EPSRC grants EP/P01013X/1 (STRETCH) and EP/R013144/1 (SAUSE) and ERC grant 291652 (ASAP).  ... 
doi:10.1016/j.procs.2019.09.214 fatcat:big3mnxpird75naynjerkmmqky

Data management research at the MITRE Corporation

Arnon Rosenthal, Len Seligman, Catherine McCollum, Barbara Blaustein, Bhavani Thuraisingham, Edward Lafferty
1995 SIGMOD record  
We would also like to thank Ron Haggarty, MITRE's Vice President for Research and Technology, for his committment to research in this area.  ...  ACKNOWLEDGMENTS The authors would like to thank Pamela Campbell, Linda Chambless, and Manette Lazear for providing ideas, project descriptions, and valuable feedback.  ...  We are investigating MLS support for important OODBMS features that are missing from earlier MLS OODBMS models.  ... 
doi:10.1145/211990.212020 fatcat:hqb7wxnpenezlbdy6rk4bx3sme

Beyond technology: Can artificial intelligence support clinical decisions in the prediction of sepsis?
Para além da tecnologia: a inteligência artificial pode apoiar decisões clínicas na predição da sepse?

Juliane de Souza Scherer, Jéssica Silveira Pereira, Mariana Severo Debastiani, Claudia Giuliano Bica
2022 Revista Brasileira de Enfermagem  
Conclusions: Far beyond technology, ML models can speed up assertive clinical decisions by nurses, optimizing time and specialized human resources.  ...  The Machine Learning (ML) tool, Robot Laura®, scores changes in vital parameters and lab tests, classifying them by severity. Inpatients and patients over 18 years of age were included.  ...  CONCLUSIONS Far beyond technology, ML models can speed up assertive clinical decisions by nurses, through critical alarms, optimizing time and specialized human resources.  ... 
doi:10.1590/0034-7167-2021-0586 fatcat:nulq5oivpff6rby2s6jsjqowma

Towards Observability for Machine Learning Pipelines [article]

Shreya Shankar, Aditya Parameswaran
2022 arXiv   pre-print
We propose a new type of data management system that offers end-to-end observability, or visibility into complex system behavior, for ML pipelines through assisted (1) detection, (2) diagnosis, and (3)  ...  and silent failures that could occur at any stage, or component, of the ML pipeline (e.g., data distribution shift).  ...  The majority of the work in data management for ML concentrates on specific components, e.g., for identifying data bugs during preprocessing [1, 2] , or for logging models and model metadata for post-hoc  ... 
arXiv:2108.13557v2 fatcat:ddgupkuskvcf5n4xhkybr5f36i

Benchmarking Safety Monitors for Image Classifiers with Machine Learning [article]

Raul Sena Ferreira
2021 arXiv   pre-print
As the prediction from the ML is the core information directly impacting safety, many works are focusing on monitoring the ML model itself.  ...  Therefore, this paper aims at establishing a baseline framework for benchmarking monitors for ML image classifiers.  ...  This technique is an adaptation of the classical program assertions to monitor and improve ML models. The idea is to verify inputs/outputs that indicate when errors may be occurring in the system.  ... 
arXiv:2110.01232v1 fatcat:t4jj7uh66vhftoiiea5eyajxma

Benchmarking Safety Monitors for Image Classifiers with Machine Learning

Raul Sena Ferreira, Jean Arlat, Jeremie Guiochet, Helene Waeselynck
2021 2021 IEEE 26th Pacific Rim International Symposium on Dependable Computing (PRDC)  
HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not.  ...  The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.  ...  This technique is an adaptation of the classical program assertions to monitor and improve ML models. The idea is to verify inputs/outputs that indicate when errors may be occurring in the system.  ... 
doi:10.1109/prdc53464.2021.00012 fatcat:wvwbz22iz5egbesdirazuxpqsm

Intravenous Lipid Emulsion Does Not Augment Blood Pressure Recovery in A Rabbit Model of Metoprolol Toxicity

Alexander Browne, Martyn Harvey, Grant Cave
2010 Journal of Medical Toxicology  
Effect for ILE has been demonstrated in animal models of propranolol poisoning; however, any benefit for ILE in more hydrophilic β-blockers remains uncertain.  ...  Twenty sedated, invasively monitored and mechanically ventilated adult New Zealand white rabbits underwent metoprolol infusion to mean arterial pressure (MAP) 60% baseline.  ...  for improvement in the latter.  ... 
doi:10.1007/s13181-010-0049-y pmid:20354918 pmcid:PMC3550458 fatcat:rtzx3ghsirdwtkkfwnvdyzhlby

Page 7 of Primary Cardiology Vol. 16, Issue 1 [page]

1990 Primary Cardiology  
The investigators assert that their two-dimensional echocardiography studies suggest that LV modeling and function are improved in patients who receive IV strepto- kinase after Mi compared with those assigned  ...  End systolic volume was signifi- cantly less (P = 0.036) for streptokinase-treated patients (65.4 + 36.4 mL) than for control patients (74.9 + 45.7 mL).  ... 

Integration of formal and heuristic reasoning as a basis for testing and debugging computer security policy

J. Bret Michael, Edgar H. Sibley, David C. Littleman
1993 Proceedings on the 1992-1993 workshop on New security paradigms - NSPW '92-93  
of information systems to these threats, especially for those aspects of information systems that are more readily amenable to modeling via non-formal methods.  ...  We present a paradigm integrating formal and heuristic reasoning as a basis for testing for and debugging computer security policy.  ...  Acknowledgements Richard Wexelblat actively participated in research meetings which produced some of the ideas which were subsequently further refined and presented in this paper.  ... 
doi:10.1145/283751.283784 dblp:conf/nspw/MichaelSL93 fatcat:bw7bnqxzgbe2fnlceqxr5rzao4

Improved Tool Support for Machine-Code Decompilation in HOL4 [chapter]

Anthony Fox
2015 Lecture Notes in Computer Science  
As a result of these improvements, decompilation is faster (on average by one to two orders of magnitude), the instruction set specifications are easier to write, and the proof tools are easier to maintain  ...  This paper presents improvements that have been made to our methodology for soundly decompiling machine-code programs to functions expressed in HOL logic.  ...  To date, L3 models have been exported to HOL4, Standard ML, Isabelle/HOL and TSL [10] .  ... 
doi:10.1007/978-3-319-22102-1_12 fatcat:xrbtb3mlrzezrddt2zrci2rl54
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