146 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. Machine Learning Algorithms for Labeling: Where and How They are Used?
14. Muscle Analyzer System: Exploring Correlation Between Novel Microwave Resonator and Ultrasound-based Tissue Information in the Thigh
15. Towards Continuous Data Collection from In-service Products: Exploring the Relation Between Data Dimensions and Collection Challenges
16. Bayesian propensity score matching in automotive embedded software engineering
17. On the Impact of ML use cases on Industrial Data Pipelines
18. On Autonomous Dynamic Software Ecosystems.
19. Assessing the Suitability of Semi-Supervised Learning Datasets using Item Response Theory
20. Size matters? Or not: A/B testing with limited sample in automotive embedded software
21. Preface of the Workshop Organizers
22. Success Factors when Transitioning to Continuous Deployment in Software-Intensive Embedded Systems
23. Towards MLOps: A Framework and Maturity Model
24. The MaLET Model — Maturity Levels for Exploratory Testing
25. AF-DNDF: Asynchronous Federated Learning of Deep Neural Decision Forests
26. End-to-End Federated Learning for Autonomous Driving Vehicles
27. An architecture for enabling A/B experiments in automotive embedded software
28. Real-time End-to-End Federated Learning: An Automotive Case Study
29. Perceived benefits of Continuous Deployment in Software-Intensive Embedded Systems
30. An Empirical Evaluation of Algorithms for Data Labeling
31. On the Experiences of Adopting Automated Data Validation in an Industrial Machine Learning Project
32. Towards Automated Detection of Data Pipeline Faults
33. AI Deployment Architecture: Multi-Case Study for Key Factor Identification
34. Principles for Re-architecting Software for Heterogeneous Platforms
35. Process Debt: a First Exploration
36. Mining Customer Satisfaction on B2B Online Platforms using Service Quality and Web Usage Metrics
37. Federated Learning Systems: Architecture Alternatives
38. DevOps for AI – Challenges in Development of AI-enabled Applications
39. Automotive A/B testing: Challenges and Lessons Learned from Practice
40. Modelling Data Pipelines
41. AI on the Edge: Architectural Alternatives
42. Software Logs for Machine Learning in a DevOps Environment
43. The Five Purposes of Value Modeling
44. Breaking the Vicious Circle: Why AI for software analytics and business intelligence does not take off in practice
45. Refactoring Software in the Automotive Domain for Execution on Heterogeneous Platforms
46. Statistical Models for the Analysis of Optimization Algorithms With Benchmark Functions.
47. Business as Unusual: A Model for Continuous Real-Time Business Insights Based on Low Level Metrics
48. Data Management Challenges for Deep Learning
49. How Regulations of Safety-Critical Software Affect Technical Debt
50. Software Challenges in Heterogeneous Computing: A Multiple Case Study in Industry
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