Materials

1 Books

Universal gradient descent. Alexander Gasnikov - (in Russian) - probably, the most comprehensive book on the modern numerical methods, which covers a lot of theoretical and practical aspects of mathematical programming.

@article{gasnikov2017universal,
  title={Universal gradient descent},
  author={Gasnikov, Alexander},
  journal={arXiv preprint arXiv:1711.00394},
  year={2017}
}
@article{bubeck2015convex,
  title={Convex optimization: Algorithms and complexity},
  author={Bubeck, Sébastien and others},
  journal={Foundations and Trends® in Machine Learning},
  volume={8},
  number={3-4},
  pages={231--357},
  year={2015},
  publisher={Now Publishers, Inc.}
}
@book{boyd2004convex,
  title={Convex optimization},
  author={Boyd, Stephen and Vandenberghe, Lieven},
  year={2004},
  publisher={Cambridge university press}
}
@book{nocedal2006numerical,
  title={Numerical optimization},
  author={Nocedal, Jorge and Wright, Stephen},
  year={2006},
  publisher={Springer Science & Business Media}
}
@book{nesterov2018lectures,
  title={Lectures on convex optimization},
  author={Nesterov, Yurii},
  volume={137},
  publisher={Springer}
}
@book{todd2016minimum,
  title={Minimum-volume ellipsoids: Theory and algorithms},
  author={Todd, Michael J},
  year={2016},
  publisher={SIAM}
}
@article{жадан2014методы,
  title={Методы оптимизации. Часть 1. Введение в выпуклый анализ и теорию оптимизации: учебное пособие},
  author={Жадан, ВГ},
  journal={М.: МФТИ},
  year={2014}
}
@article{жадан2015методы,
  title={Методы оптимизации. Часть 2. Численные алгоритмы: учебное пособие},
  author={Жадан, ВГ},
  journal={М.: МФТИ},
  year={2015}
}

2 Courses

3 Blogs and personal pages

  • I’m a bandit blog by Sébastien Bubeck.
  • Blog by Moritz Hardt.
  • Blog by Sebastian Pokutta with great cheat sheets on optimization.
  • Blog by Sebastian Ruder about NLP and optimization.
  • Personal page of Peter Richtarik with announcements and news.
  • Personal page of Suvrit Sra.
  • Blog by Fabian Pedregosa.
  • Blog with beatiful insights about modern non-convex optimization.
  • Machine Learning Research Blog by Francis Bach.

4 Software and apps

5 Other