Corpus ID: 8825075

How I won the "Chess Ratings - Elo vs the Rest of the World" Competition

@article{Sismanis2010HowIW,
  title={How I won the "Chess Ratings - Elo vs the Rest of the World" Competition},
  author={Yannis Sismanis},
  journal={ArXiv},
  year={2010},
  volume={abs/1012.4571}
}
This article discusses in detail the rating system that won the kaggle competition “Chess Ratings: Elo vs the rest of the world”. The competition provided a historical dataset of outcomes for chess games, and aimed to discover whether novel approaches can predict the outcomes of future games, more accurately than the well-known Elo rating system. The winning rating system, called Elo++ in the rest of the article, builds upon the Elo rating system. Like Elo, Elo++ uses a single rating per player… Expand
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References

SHOWING 1-5 OF 5 REFERENCES
Introduction to Stochastic Search and Optimization
TLDR
A survey of the range of topics, in a strong, interdisciplinary format that will appeal to both students and researchers. Expand
A Limited Memory Algorithm for Bound Constrained Optimization
An algorithm for solving large nonlinear optimization problems with simple bounds is described. It is based on the gradient projection method and uses a limited memory BFGS matrix to approximate theExpand
Chess Rating Systems
  • Chess Rating Systems
Kaggle Contest: Chess Ratings ELO vs the World
  • Kaggle Contest: Chess Ratings ELO vs the World
Kaggle Contest: Chess Ratings — Elo vs the Rest of the World
  • Kaggle Contest: Chess Ratings — Elo vs the Rest of the World