aboutsummaryrefslogtreecommitdiffstats
path: root/paper/sections/discussion.tex
diff options
context:
space:
mode:
Diffstat (limited to 'paper/sections/discussion.tex')
-rw-r--r--paper/sections/discussion.tex2
1 files changed, 1 insertions, 1 deletions
diff --git a/paper/sections/discussion.tex b/paper/sections/discussion.tex
index 03e7ff2..2f0fd36 100644
--- a/paper/sections/discussion.tex
+++ b/paper/sections/discussion.tex
@@ -17,7 +17,7 @@ This model therefore falls into the 1-bit compressed sensing framework
\cite{Boufounos:2008}. Several recent papers study the theoretical
guarantees obtained for 1-bit compressed sensing with specific measurements
\cite{Gupta:2010, Plan:2014}. Whilst they obtained bounds of the order
-${\cal O}(n \log \frac{m}{s}$), no current theory exists for recovering
+${\cal O}(s \log \frac{m}{s}$), no current theory exists for recovering
positive bounded signals from binary measurememts. This research direction
may provide the first clues to solve the ``adaptive learning'' problem: if we
are allowed to adaptively \emph{choose} the source nodes at the beginning of