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| author | Thibaut Horel <thibaut.horel@gmail.com> | 2013-02-11 20:21:42 -0800 |
|---|---|---|
| committer | Thibaut Horel <thibaut.horel@gmail.com> | 2013-02-11 20:21:42 -0800 |
| commit | 05072094652d9587c22364d50ab8f004479ca900 (patch) | |
| tree | c47b51007f07d349bb2a1688139d8107793e4619 /main.tex | |
| parent | 7f6e240cf4c111449cc2fceae13a0925fc95192a (diff) | |
| download | recommendation-05072094652d9587c22364d50ab8f004479ca900.tar.gz | |
Small fix
Diffstat (limited to 'main.tex')
| -rw-r--r-- | main.tex | 2 |
1 files changed, 1 insertions, 1 deletions
@@ -90,7 +90,7 @@ The function $L$ is well-known to be concave and even self-concordant (see method for self-concordant functions in \cite{boyd2004convex}, shows that finding the maximum of $L$ to any precision $\varepsilon$ can be done in $O(\log\log\varepsilon^{-1})$ iterations. Being the solution to a maximization -problem, $L^*$ satisfies the required monotonicity property. The main challenge +problem, $OPT'_{-i^*}$ satisfies the required monotonicity property. The main challenge will be to prove that $OPT'_{-i^*}$, for our relaxation $L$, is close to $OPT_{-i^*}$. |
