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Are Concept Drift Detectors Reliable Alarming Systems? -- A Comparative Study
We compare the performance of the most popular drift detectors belonging to two different concept drift detector groups, error rate-based detectors and data distribution-based detectors.
Roadmap for Edge AI: A Dagstuhl Perspective
Based on the collective input of Dagstuhl Seminar (21342), this paper presents a comprehensive discussion on AI methods and capabilities in the context of edge computing, referred as Edge AI.
RCURRENCY: Live Digital Asset Trading Using a Recurrent Neural Network-based Forecasting System
Evaluation of the system through backtesting shows that RCURRENCY can be used to successfully not only maintain a stable portfolio of digital assets in a simulated live environment using real historical trading data but even increase the portfolio value over time.
Systematic Mapping Study on the Machine Learning Lifecycle
However, the advent of AI is bringing an increasing set of practical problems related to AI model lifecycle management that need to be investigated.
A Survey on Distributed Machine Learning
The demand for artificial intelligence has grown significantly over the last decade and this growth has been fueled by advances in machine learning techniques and the ability to leverage hardware acceleration.
