@InProceedings{chen_et_al:LIPIcs.APPROX-RANDOM.2019.64,
  author =	{Chen, Zongchen and Vempala, Santosh S.},
  title =	{{Optimal Convergence Rate of Hamiltonian Monte Carlo for Strongly Logconcave Distributions}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2019)},
  pages =	{64:1--64:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-125-2},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{145},
  editor =	{Achlioptas, Dimitris and V\'{e}gh, L\'{a}szl\'{o} A.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX-RANDOM.2019.64},
  URN =		{urn:nbn:de:0030-drops-112790},
  doi =		{10.4230/LIPIcs.APPROX-RANDOM.2019.64},
  annote =	{Keywords: logconcave distribution, sampling, Hamiltonian Monte Carlo, spectral gap, strong convexity}
}