%0 Journal Article %1 Hsu_Kakade_Zhang_2012 %A Hsu, Daniel %A Kakade, Sham M. %A Zhang, Tong %D 2012 %I Institute of Mathematical Statistics %J Electronic Communications in Probability %K hanson.wright quadratic_forms subgaussian tail_bounds %N 0 %R 10.1214/ECP.v17-2079 %T A tail inequality for quadratic forms of subgaussian random vectors %V 17 %X This article proves an exponential probability tail inequality for positive semidefinite quadratic forms in a subgaussian random vector. The bound is analogous to one that holds when the vector has independent Gaussian entries.

@article{Hsu_Kakade_Zhang_2012, abstract = {This article proves an exponential probability tail inequality for positive semidefinite quadratic forms in a subgaussian random vector. The bound is analogous to one that holds when the vector has independent Gaussian entries.}, added-at = {2013-10-18T04:01:18.000+0200}, author = {Hsu, Daniel and Kakade, Sham M. and Zhang, Tong}, biburl = {https://www.bibsonomy.org/bibtex/257faca011070c05277c643cf9f66294c/ytyoun}, doi = {10.1214/ECP.v17-2079}, interhash = {a28835078ba44a1b200686e00d6ce1c6}, intrahash = {57faca011070c05277c643cf9f66294c}, journal = {Electronic Communications in Probability}, keywords = {hanson.wright quadratic_forms subgaussian tail_bounds}, month = jan, number = 0, publisher = {Institute of Mathematical Statistics}, timestamp = {2013-10-18T04:01:18.000+0200}, title = {A tail inequality for quadratic forms of subgaussian random vectors}, volume = 17, year = 2012 }