last changes

1 files changed, 15 insertions, 28 deletions

diff --git a/paper/rebuttal.txt b/paper/rebuttal.txt
index 91a3cf5..2ab98e2 100644
--- a/paper/rebuttal.txt
+++ b/paper/rebuttal.txt
@@ -1,18 +1,14 @@
 We would like to thank the reviewers for carefully reading our paper and their
-insightful remarks. It seems that most of the major points raised by the
-reviewers are due to ambiguity in our presentation, which can easily be
-addressed by including a couple of paragraphs of clarifying text. If
-appropriate, we would be happy to include these clarifications in the
-manuscript and have a reviewer shepherd our paper to ensure we indeed address
-all the comments raised.
+insightful remarks. We have tried to address the main points of contention
+below:
 
 R2:
 "
 The set of parameters \theta always lies in some constrained space. For
-example, in the independent cascade model, \theta_{i,j} < 0; in the voter
-model, \sum_{i,j} \theta = 1 and \theta_{i,i} \neq 0.[...] authors would have
-(norm_1 + regularization induced by constraints), which is not really clear
-whether is decomposable or not.
+example, in the independent cascade model, θ_{i,j} < 0; in the voter model,
+∑_{i,j} θ_{i,i} = 1 and θ_{i,i}≠0.[...] authors would have (norm_1 +
+regularization induced by constraints), which is not really clear whether is
+decomposable or not.
 "
 
 This is a great point and we should have been more explicit about this. Overall
@@ -52,8 +48,7 @@ attempts
 As the reviewer correctly points out, the standard ICC model does not allow
 for multiple infection attempts over time. The definition of section 2.2.1 also
 prohibits multiple attempts by considering that nodes stay active for only one
-time step, defining X_t as the set of nodes active at the previous time step
-only, and saying that only nodes which have not been infected before are
+time step and saying that only nodes which have not been infected before are
 susceptible to be infected.
 
 R3:
@@ -67,7 +62,6 @@ different points in the graph. Despite the fact that the infected nodes from
 each cascade will not overlap, we cannot in practice attribute an infected node
 to either cascade because we don't know which source is closer to it.
 
-
 "
 The inference in discrete time, one-time-susceptible contagion
 processes is less interesting and easier than the continuous version.
@@ -78,17 +72,14 @@ processes (such as the linear voter model). Furthermore, it is not immediately
 clear that discrete-time processes cannot approximate some continuous time
 processes efficiently. For example, we can discretize the continuous time
 process of Gomez-Rodriguez et al. 2011 with exponential transmission likelihood
-by considering intervals of time of length dt, binning infections to these
-intervals, and considering that nodes remain infected until the final
-observation time. By the exponential distribution's memorylessness, it can be
-shown that when dt<<1, the problem is still decomposable and fits into the
-Generalized Linear Cascade model framework.
-
-We agree that it should be made clear in the definition of cascade models that
-we mean discrete-time cascades, and that running time comparison of different
-algorithms should be added. Indeed, the MLE from NS has the same running time
-as the penalized MLE, but both are slower than the more naive greedy algorithm.
+by binning infections to regular intervals of size dt. By the exponential
+distribution's memorylessness, it can be shown that when dt<<1, the problem is
+still decomposable and fits into the Generalized Linear Cascade model
+framework.
 
+We agree with the remark that the definition of cascade models should specify
+that this holds only for discrete-time cascades, and that running time
+comparison of different algorithms should be added.
 
 R4:
 Reviewer 4 raised the point of showing expected performance given some
@@ -98,13 +89,9 @@ Finally, we agree that showing "at least one common metric for all
 types of graph" should be added to the experimental section.
 
 Misc.
-"
-Citations/Related work remarks
-"
 The requested citations can be included on lines 42, 68, 75, 78, 93, 362. The
 authors regret not to have cited Du et al. 2012 and their work should be
-included in the related work section along with other work considering the
-estimation of influence in networks. It can be mentioned that Daneshmand et al
+included in the related work section. It can be mentioned that Daneshmand et al
 adopt the same model as Gomez-R et al '10 and Abrahao et al. '13.  The phrasing
 can be changed from "Graph Inference" to "Network Inference" with the requested
 citations.