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Neuronale Netze und Künstliche Intelligenz, Maschinelles Lernen,    Algorithmen und Datenstrukturen

ICMS - International Centre for Mathematical Sciences

In recent years, the field of machine learning (ML) has seen tremendous progress, with many breakthroughs directly connected to the well-studied mathematical theory of Stochastic Differential Equations (SDEs). This increasingly fruitful relationship between SDEs and ML has produced several state-of-the-art innovations, ranging from Langevin algorithms in Bayesian learning to score-based diffusion models in computer vision. This workshop aims to bring the SDE and ML communities closer together and “sow the seeds” for future interdisciplinary and impactful research.

SDE-inspired learning algorithms and architectures • Computational or learning-based algorithms for SDEs • Theoretical connections between SDEs and machine learning • Applications and areas of opportunity between disciplines

6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances.

Email: cmla@cseit2024.org

Bayesian Network Computer Vision Data Mining Deep Learning Learning in knowledge-intensive systems Learning Methods and analysis Learning Problems Machine Learning Algorithms Neural Networks Predictive Learning Reinforcement Learning Supervised Machine Learning Unsupervised Machine Learning

Neuronale Netze und Künstliche Intelligenz, Maschinelles Lernen,    Mustererkennung und Bildverarbeitung, Maschinelles Sehen