202 results on '"Bosch, Jan"'
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2. Advancing MLOps from Ad hoc to Kaizen
3. All data is equal or is some data more equal? On strategic data collection and use in the embedded systems domain
4. Multi-Agent Reinforcement Learning in Dynamic Industrial Context
5. Deep Reinforcement Learning for Multiple Agents in a Decentralized Architecture: A Case Study in the Telecommunication Domain
6. Autonomous Navigation and Configuration of Integrated Access Backhauling for UAV Base Station Using Reinforcement Learning
7. The Role Of Post-Release Software Traceability in Release Engineering: A Software-Intensive Embedded Systems Case Study From The Telecommunications Domain
8. Living in a Pink Cloud or Fighting a Whack-a-Mole? On the Creation of Recurring Revenue Streams in the Embedded Systems Domain
9. Deep Reinforcement Learning in a Dynamic Environment: A Case Study in the Telecommunication Industry
10. Pattern Recognition Method for Detecting Engineering Errors on Technical Drawings
11. Challenges in developing and deploying AI in the engineering, procurement and construction industry
12. Customer Support In The Era of Continuous Deployment: A Software-Intensive Embedded Systems Case Study
13. Controlled Continuous Deployment: A Case Study From The Telecommunications Domain
14. The goldilocks framework
15. Machine Learning Algorithms for Labeling: Where and How They are Used?
16. Muscle Analyzer System: Exploring Correlation Between Novel Microwave Resonator and Ultrasound-based Tissue Information in the Thigh
17. Towards Continuous Data Collection from In-service Products: Exploring the Relation Between Data Dimensions and Collection Challenges
18. Bayesian propensity score matching in automotive embedded software engineering
19. On the Impact of ML use cases on Industrial Data Pipelines
20. Assessing the Suitability of Semi-Supervised Learning Datasets using Item Response Theory
21. Size matters? Or not: A/B testing with limited sample in automotive embedded software
22. Preface of the Workshop Organizers
23. Success Factors when Transitioning to Continuous Deployment in Software-Intensive Embedded Systems
24. Towards MLOps: A Framework and Maturity Model
25. The MaLET Model — Maturity Levels for Exploratory Testing
26. AF-DNDF: Asynchronous Federated Learning of Deep Neural Decision Forests
27. End-to-End Federated Learning for Autonomous Driving Vehicles
28. An architecture for enabling A/B experiments in automotive embedded software
29. Real-time End-to-End Federated Learning: An Automotive Case Study
30. Perceived benefits of Continuous Deployment in Software-Intensive Embedded Systems
31. An Empirical Evaluation of Algorithms for Data Labeling
32. On the Experiences of Adopting Automated Data Validation in an Industrial Machine Learning Project
33. Towards Automated Detection of Data Pipeline Faults
34. AI Deployment Architecture: Multi-Case Study for Key Factor Identification
35. Principles for Re-architecting Software for Heterogeneous Platforms
36. Process Debt: a First Exploration
37. Mining Customer Satisfaction on B2B Online Platforms using Service Quality and Web Usage Metrics
38. Federated Learning Systems: Architecture Alternatives
39. DevOps for AI – Challenges in Development of AI-enabled Applications
40. Automotive A/B testing: Challenges and Lessons Learned from Practice
41. Modelling Data Pipelines
42. AI on the Edge: Architectural Alternatives
43. Software Logs for Machine Learning in a DevOps Environment
44. The Five Purposes of Value Modeling
45. Breaking the Vicious Circle: Why AI for software analytics and business intelligence does not take off in practice
46. Refactoring Software in the Automotive Domain for Execution on Heterogeneous Platforms
47. Carrot and stick approaches when managing technical debt
48. Developing ML/DL Models
49. From Ad-Hoc Data Analytics to DataOps
50. Experimentation for Business-to-Business Mission-Critical Systems
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