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International Conference on Statistical Techniques for Machine Learning and AI - (ICSTMMLA-27)

10th - 11th February 2027 , Doha - Qatar

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Call For Papers

The (ICSTMMLA-27) emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Statistics, Data Science are explored to promote cross-domain knowledge exchange and collaborative innovation.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Machine learning algorithms for statistical analysis
  • Statistical techniques in AI model evaluation
  • Feature selection methods in machine learning
  • Statistical learning theory applications
  • Data preprocessing for machine learning models
  • Ensemble methods in statistical learning
  • Deep learning and statistical inference
  • Bayesian statistics in AI applications
  • Statistical methods for big data analytics
  • Interpretability of machine learning models
  • Statistical challenges in AI deployment
  • Reinforcement learning and statistical methods
  • Statistical evaluation of AI systems
  • Transfer learning in statistical contexts
  • Statistical methods for time series analysis
  • Unsupervised learning and statistical techniques
  • Statistical issues in data privacy
  • Statistical frameworks for AI ethics
  • Applications of statistics in natural language processing
  • Statistical modeling of complex systems

Assessment

All submissions will undergo peer review to ensure quality and interdisciplinary relevance. Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.

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