(ICSLMLI - 26) | Hybrid Event
26th - 27th December 2026 | Los Angeles, USA

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International Conference on Statistical Learning and Machine Learning Integration
(ICSLMLI - 26)

26th - 27th December 2026 Los Angeles, USA (Hybrid Event)

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Call for Paper

The ICSLMLI is committed to addressing global challenges through impactful research and sustainable solutions. It brings together researchers dedicated to advancing knowledge for societal benefit. Focusing on Statistics, the conference promotes research aligned with global development goals and long-term sustainability. Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Integration of statistical learning and machine learning
  • Applications of machine learning in statistics
  • Statistical methods for predictive modeling
  • Bayesian statistics and machine learning synergy
  • Statistical learning techniques for big data
  • Feature selection methods in statistical learning
  • Statistical validation of machine learning models
  • Deep learning applications in statistical analysis
  • Statistical approaches to model interpretability
  • Ensemble methods in statistical learning
  • Statistical methods for time series forecasting
  • Applications of neural networks in statistics
  • Statistical learning in bioinformatics
  • Causal inference in machine learning contexts
  • Statistical frameworks for unsupervised learning
  • Statistical software for machine learning applications
  • Challenges in integrating statistics and machine learning
  • Statistical methods for anomaly detection
  • Ethics in statistical machine learning applications
  • Future directions in statistical learning research
Review & Publication

All submissions will be reviewed for their contribution to global impact and research quality. Accepted papers will be presented and considered for publication in reputed platforms.

Registration

Join participants from around the world by completing your registration and becoming part of a global research community.

Publication

Accepted papers will gain international exposure through conference presentations and publication opportunities.

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