Andrej Risteski, Yuanzhi Li. Approximate maximum entropy principles via Goemans-Williamson with applications to provable variational methods. In Daniel D. Lee, Masashi Sugiyama, Ulrike V. Luxburg, Isabelle Guyon, Roman Garnett, editors, Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain. pages 4628-4636, 2016. [doi]
@inproceedings{RisteskiL16,
title = {Approximate maximum entropy principles via Goemans-Williamson with applications to provable variational methods},
author = {Andrej Risteski and Yuanzhi Li},
year = {2016},
url = {http://papers.nips.cc/paper/6169-approximate-maximum-entropy-principles-via-goemans-williamson-with-applications-to-provable-variational-methods},
researchr = {https://researchr.org/publication/RisteskiL16},
cites = {0},
citedby = {0},
pages = {4628-4636},
booktitle = {Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain},
editor = {Daniel D. Lee and Masashi Sugiyama and Ulrike V. Luxburg and Isabelle Guyon and Roman Garnett},
}