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-rw-r--r--notes/images/drawing.svg807
-rw-r--r--notes/images/icc_model.svg361
-rw-r--r--notes/images/noedges_step1.svg633
-rw-r--r--notes/images/voter_model.svg446
-rw-r--r--paper/sparse.bib11
-rw-r--r--poster/CS284r_poster/beamerthemeconfposter.sty (renamed from poster/beamerthemeconfposter.sty)0
-rw-r--r--poster/CS284r_poster/cracking_cascades_classposter.tex (renamed from poster/cracking_cascades_classposter.tex)0
-rw-r--r--poster/WWW_poster/beamerthemeconfposter.sty184
-rw-r--r--poster/WWW_poster/poster.tex289
-rw-r--r--poster/images/SEASLogo_RGB.pngbin0 -> 35972 bytes
-rw-r--r--src/algorithms.py6
-rw-r--r--src/cascade_creation.py6
-rw-r--r--src/convex_optimization.py4
-rw-r--r--src/make_plots.py18
14 files changed, 2747 insertions, 18 deletions
diff --git a/notes/images/drawing.svg b/notes/images/drawing.svg
new file mode 100644
index 0000000..9aaf8a0
--- /dev/null
+++ b/notes/images/drawing.svg
@@ -0,0 +1,807 @@
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diff --git a/paper/sparse.bib b/paper/sparse.bib
index 4aee818..81b493e 100644
--- a/paper/sparse.bib
+++ b/paper/sparse.bib
@@ -24,7 +24,13 @@ year = {2006},
numpages = {10},
publisher = {ACM},
address = {New York, NY, USA},
-}
+}
+
+@inproceedings{Pouget:2015,
+ title={Inferring graphs from cascades: A Sparse Recovery Framework},
+ author={Pouget-Abadie, Jean and Horel, Thibaut},
+ series={ICML'15}
+}
@article{Netrapalli:2012,
@@ -36,7 +42,6 @@ year = {2006},
month = {June},
year = {2012},
issn = {0163-5999},
- pages = {211--222},
numpages = {12},
publisher = {ACM},
address = {New York, NY, USA},
@@ -550,3 +555,5 @@ year = "2009"
year={2005},
publisher={Springer}
}
+
+
diff --git a/poster/beamerthemeconfposter.sty b/poster/CS284r_poster/beamerthemeconfposter.sty
index bcba6a7..bcba6a7 100644
--- a/poster/beamerthemeconfposter.sty
+++ b/poster/CS284r_poster/beamerthemeconfposter.sty
diff --git a/poster/cracking_cascades_classposter.tex b/poster/CS284r_poster/cracking_cascades_classposter.tex
index 3f8204e..3f8204e 100644
--- a/poster/cracking_cascades_classposter.tex
+++ b/poster/CS284r_poster/cracking_cascades_classposter.tex
diff --git a/poster/WWW_poster/beamerthemeconfposter.sty b/poster/WWW_poster/beamerthemeconfposter.sty
new file mode 100644
index 0000000..bcba6a7
--- /dev/null
+++ b/poster/WWW_poster/beamerthemeconfposter.sty
@@ -0,0 +1,184 @@
+%==============================================================================
+% Beamer style for the poster template posted at
+% www.nathanieljohnston.com/index.php/2009/08/latex-poster-template
+%
+% Created by the Computational Physics and Biophysics Group at Jacobs University
+% https://teamwork.jacobs-university.de:8443/confluence/display/CoPandBiG/LaTeX+Poster
+% Modified by Nathaniel Johnston (nathaniel@nathanieljohnston.com) in August 2009
+% =============================================================================
+
+\ProvidesPackage{beamerthemeconfposter}
+\RequirePackage{tikz} % for drawing the nice rounded boxes
+\usetikzlibrary{arrows,backgrounds}
+\RequirePackage[T1]{fontenc}
+\RequirePackage{lmodern}
+\RequirePackage{textcomp}
+\RequirePackage{amsmath,amssymb}
+\usefonttheme{professionalfonts}
+\newcommand{\makeruleinbox}{{\usebeamercolor[bg]{block alerted title}\centering\hspace*{-0.7cm}\rule{\inboxrule}{0.5cm}}}
+\usepackage{ragged2e}
+\usepackage{wrapfig}
+%-----------------------------------------------------------
+% Define a whole bunch of custom colours and fonts
+%-----------------------------------------------------------
+
+\definecolor{lgreen} {RGB}{180,210,100}
+\definecolor{dblue} {RGB}{20,66,129}
+\definecolor{ddblue} {RGB}{11,36,69}
+\definecolor{lred} {RGB}{220,0,0}
+\definecolor{nred} {RGB}{224,0,0}
+\definecolor{norange}{RGB}{244,127,36}
+\definecolor{nyellow}{RGB}{255,221,0}
+\definecolor{ngreen} {RGB}{98,158,31}
+\definecolor{dgreen} {RGB}{78,138,21}
+\definecolor{nblue} {RGB}{28,130,185}
+\definecolor{jblue} {RGB}{20,50,100}
+\definecolor{jalpha} {RGB}{0,0,0}
+
+% set the basic colors
+\setbeamercolor{palette primary} {fg=black,bg=white}
+\setbeamercolor{palette secondary} {fg=black,bg=white}
+\setbeamercolor{palette tertiary} {bg=jblue,fg=white}
+\setbeamercolor{palette quaternary}{fg=black,bg=white}
+\setbeamercolor{structure}{fg=jblue}
+\setbeamercolor{titlelike} {bg=jblue,fg=white}
+\setbeamercolor{frametitle} {bg=jblue!10,fg=jblue}
+\setbeamercolor{cboxb}{fg=black,bg=jblue}
+\setbeamercolor{cboxr}{fg=black,bg=red}
+
+% set colors for itemize/enumerate
+\setbeamercolor{item}{fg=ngreen}
+\setbeamercolor{item projected}{fg=white,bg=ngreen}
+
+% set colors for blocks
+%\setbeamercolor{block title}{fg=ngreen,bg=white}
+%\setbeamercolor{block body}{fg=black,bg=white}
+
+%set colors for alerted blocks (blocks with frame)
+\setbeamercolor{block alerted title}{fg=white,bg=jblue}
+\setbeamercolor{block alerted body}{fg=black,bg=jblue!10}
+
+% set the fonts
+\setbeamerfont{section in head/foot}{series=\bfseries}
+\setbeamerfont{block title}{series=\bfseries}
+\setbeamerfont{block alerted title}{series=\bfseries}
+\setbeamerfont{frametitle}{series=\bfseries}
+\setbeamerfont{frametitle}{size=\Large}
+
+% set some beamer theme options
+\setbeamertemplate{title page}[default][colsep=-4bp,rounded=true]
+\setbeamertemplate{sections/subsections in toc}[square]
+\setbeamertemplate{items}[circle]
+\setbeamertemplate{blocks}[width=0.0]
+\beamertemplatenavigationsymbolsempty
+
+% set bibliography style
+\setbeamertemplate{bibliography item}[text]
+\setbeamercolor{bibliography item}{fg=black,bg=white}
+\setbeamercolor{bibliography entry author}{fg=black,bg=white}
+\setbeamercolor{bibliography item}{fg=black,bg=white}
+
+% define some length variables that are used by the template
+\newlength{\inboxwd}
+\newlength{\iinboxwd}
+\newlength{\inboxrule}
+\makeatletter
+\makeatother
+
+%==============================================================================
+% build the poster title
+%==============================================================================
+\setbeamertemplate{headline}{
+ \leavevmode
+ \begin{columns}
+ \begin{column}{.2\linewidth}
+ \vskip1cm
+ \centering
+ %\includegraphics[height=4in]{UIUC-logo}
+ \end{column}
+ \vspace{1cm}
+ \begin{column}{.6\linewidth}
+ \vskip1cm
+ \centering
+ \usebeamercolor{title in headline}{\color{jblue}\Huge{\textbf{\inserttitle}}\\[0.5ex]}
+ \usebeamercolor{author in headline}{\color{fg}\Large{\insertauthor}\\[1ex]}
+ \usebeamercolor{institute in headline}{\color{fg}\large{\insertinstitute}\\[1ex]}
+ \vskip1cm
+ \end{column}
+ \vspace{1cm}
+ \begin{column}{.2\linewidth}
+ \vskip1cm
+ \centering
+ %\includegraphics[height=4in]{graph500-logo}
+ \vskip1cm
+ \end{column}
+ \vspace{1cm}
+ \end{columns}
+ \vspace{0.5in}
+ \hspace{0.5in}\begin{beamercolorbox}[wd=47in,colsep=0.15cm]{cboxb}\end{beamercolorbox}
+ \vspace{0.1in}
+}
+
+% Block definition
+\setbeamertemplate{block begin}
+{
+ \par\vskip\medskipamount
+ \begin{beamercolorbox}[colsep*=0ex,dp={2ex},center]{block title}
+ \vskip-0.25cm
+ \usebeamerfont{block title}\large\insertblocktitle
+ \begin{flushleft}
+ \vskip-1cm
+ \begin{tikzpicture}[remember picture,overlay]
+ \shade [inner color=gray,outer color=white]
+ (0,0) rectangle (\textwidth,0.3cm);
+ \end{tikzpicture}
+ \end{flushleft}
+ \end{beamercolorbox}
+ {\parskip0pt\par}
+ \ifbeamercolorempty[bg]{block title}
+ {}
+ {\ifbeamercolorempty[bg]{block body}{}{\nointerlineskip\vskip-0.5pt}}
+ \usebeamerfont{block body}
+ \vskip-0.5cm
+ \begin{beamercolorbox}[colsep*=0ex,vmode]{block body}
+ \justifying
+}
+
+\setbeamertemplate{block end}
+{
+ \end{beamercolorbox}
+ \vskip\smallskipamount
+}
+
+% Alert block definition (with frame)
+\setbeamertemplate{block alerted begin}
+{
+ \par\vskip\medskipamount
+ \begin{beamercolorbox}[sep=0ex,rounded=true,center,dp={2ex}]{block alerted title}
+ \vskip0.01cm
+ \usebeamerfont{block title}\large\insertblocktitle
+ \end{beamercolorbox}
+ {\parskip0pt\par}
+ \usebeamerfont{block body}
+ \vskip-0.8cm
+ \begin{beamercolorbox}[sep=0.5cm, rounded=true,center]{block alerted title}
+ \setlength{\inboxwd}{\linewidth}
+ \addtolength{\inboxwd}{-1cm}
+ \begin{beamercolorbox}[rounded=true,wd={\inboxwd},center]{block alerted body}
+ \setlength{\iinboxwd}{\inboxwd}
+ \setlength{\inboxrule}{\inboxwd}
+ \addtolength{\iinboxwd}{-0.5cm}
+ \addtolength{\inboxrule}{0.5cm}
+ \begin{center}
+ \begin{minipage}{\iinboxwd}
+ \justifying
+}
+
+\setbeamertemplate{block alerted end}
+{
+ \end{minipage}
+ \end{center}
+ \end{beamercolorbox}
+ \end{beamercolorbox}
+ \vskip\smallskipamount
+} \ No newline at end of file
diff --git a/poster/WWW_poster/poster.tex b/poster/WWW_poster/poster.tex
new file mode 100644
index 0000000..eeee7b6
--- /dev/null
+++ b/poster/WWW_poster/poster.tex
@@ -0,0 +1,289 @@
+\documentclass[final]{beamer}
+\usepackage[utf8]{inputenc}
+\usepackage[scale=1.6]{beamerposter} % Use the beamerposter package for laying
+\usetheme{confposter} % Use the confposter theme supplied with this template
+
+\usepackage{framed, amsmath, amsthm, amssymb}
+\usepackage{color, bbm}
+\setbeamercolor{block title}{fg=dblue,bg=white} % Colors of the block titles
+\setbeamercolor{block body}{fg=black,bg=white} % Colors of the body of blocks
+\setbeamercolor{block alerted title}{fg=white,bg=dblue!70} % Colors of the
+\setbeamercolor{block alerted body}{fg=black,bg=dblue!10} % Colors of the body
+
+\newlength{\sepwid}
+\newlength{\onecolwid}
+\newlength{\twocolwid}
+\newlength{\threecolwid}
+\setlength{\paperwidth}{48in} % A0 width: 46.8in
+\setlength{\paperheight}{40in} % A0 height: 33.1in
+\setlength{\sepwid}{0.024\paperwidth} % Separation width (white space) between
+\setlength{\onecolwid}{0.22\paperwidth} % Width of one column
+\setlength{\twocolwid}{0.464\paperwidth} % Width of two columns
+\setlength{\threecolwid}{0.708\paperwidth} % Width of three columns
+\setlength{\topmargin}{-1in} % Reduce the top margin size
+%-----------------------------------------------------------
+
+\usepackage{graphicx}
+\usepackage{booktabs}
+
+%----------------------------------------------------------------------------------------
+% TITLE SECTION
+%----------------------------------------------------------------------------------------
+
+\title{Inferring Graphs from Cascades} % Poster title
+
+\author{Jean Pouget-Abadie, Thibaut Horel} % Author(s)
+
+\institute{Harvard University} % Institution(s)
+%----------------------------------------------------------------------------------------
+\begin{document}
+\addtobeamertemplate{block end}{}{\vspace*{2ex}} % White space under blocks
+\addtobeamertemplate{block alerted end}{}{\vspace*{2ex}} % White space under
+
+\setlength{\belowcaptionskip}{2ex} % White space under figures
+\setlength\belowdisplayshortskip{2ex} % White space under equations
+
+\begin{frame}[t]
+\begin{columns}[t]
+\begin{column}{\sepwid}\end{column}
+\begin{column}{\onecolwid} % The first column
+
+%----------------------------------------------------------------------------------------
+% INTODUCTION
+%----------------------------------------------------------------------------------------
+
+
+\vspace{- 12.2 cm}
+\begin{center}
+{\includegraphics[scale=2.5]{../images/SEASLogo_RGB.png}}
+\end{center}
+
+\vspace{5 cm}
+
+\begin{block}{Problem Statement}
+
+\begin{itemize}
+ \item A {\bf diffusion process} describes the evolution of a behavior, which
+ is transmitted from node to node along the edges of a network.
+ \item If the network is {\bf unknown} and only the behaviors of nodes in time
+ is observed, for which diffusion processes can we recover the edges? In
+ how many measurements?
+\end{itemize}
+
+{\bf Notation}
+\begin{itemize}
+ \item $X^t_c \in {\{0,1\}}^n$ set of infected nodes at time $t$ in cascade $c$
+ \item $p_{i,j}$: weight of directed edge $i\rightarrow j$
+\end{itemize}
+
+{\bf Objective}
+\begin{itemize}
+ \item We observe $(c, t, X^t_c)$
+ \item Find $\hat p$ such that $\|p - \hat p\|_2 \leq \epsilon$
+\end{itemize}
+
+\end{block}
+
+\begin{block}{Independent Cascade Model~\cite{Kempe:03}}
+
+\begin{figure}
+\centering
+\includegraphics[width=0.6\textwidth]{../images/voter.png}
+\end{figure}
+
+\begin{itemize}
+ \item Probability that $j^{th}$ node gets infected:
+ \begin{framed}
+ \begin{align*}
+ \tag{IC}
+ \mathbb{P}\big[X^{t+1}_j = 1\,|\, X^{t}\big]
+ & = 1 - \prod_{i = 1}^m {(1 - p_{i,j})}^{X^t_i} \\
+ & = 1 - \prod_{i = 1}^m e^{\Theta_{i,j}X^t_i} \\
+ & = 1 - e^{\Theta_j \cdot X^t}
+ \end{align*}
+ \end{framed}
+ where $\Theta_{i,j} \equiv \log(1- p_{i,j})$
+\end{itemize}
+
+\end{block}
+
+\end{column} % End of the first column
+
+%-----------------------------------------------------------------------------
+\begin{column}{\sepwid}\end{column} % Empty spacer column
+%-----------------------------------------------------------------------------
+\begin{column}{\onecolwid} % The first column
+
+\begin{block}{Voter Model}
+\begin{figure}
+\centering
+\includegraphics[width=0.6\textwidth]{../images/icc.png}
+\end{figure}
+
+\begin{itemize}
+ \item Probability that $j^{th}$ node gets infected:
+ \begin{framed}
+ \begin{equation*}
+ \tag{VT}
+ \mathbb{P}\big[X^{t+1}_j = 1\,|\, X^{t}\big]
+ = \sum_{i \in X^t} p_{i,j} = p_j \cdot X^t
+ \end{equation*}
+ \end{framed}
+\end{itemize}
+
+\end{block}
+
+
+\begin{block}{Reformulation}
+
+{\bf Generalized Linear Cascade Model}
+\begin{itemize}
+ \item $f: \mathbb{R} \rightarrow [0,1]$: inverse link function
+ \item Probability depends on $f$-transform of scalar product:
+ \begin{framed}
+ $$\mathbb{P}(X^{t+1}_j = 1 | X^t) = f(\Theta_j \cdot X^t)$$
+ \end{framed}
+\end{itemize}
+
+{\bf Setup}
+\begin{figure}
+ \centering
+ \includegraphics[scale=1.5]{../images/drawing.pdf}
+\end{figure}
+
+{\bf Examples:}
+\begin{itemize}
+ \item Independent Cascade (IC) Model: $f : z \mapsto 1-e^z$
+ \item Voter model: $f : z \mapsto z$
+ \item Discrete-version of continuous IC model~\cite{GomezRodriguez:2010}
+ \item Logistic cascades: $f: z\mapsto \frac{1}{1-e^z}$
+\end{itemize}
+
+\end{block}
+\end{column}
+%-----------------------------------------------------------------------------
+\begin{column}{\sepwid}\end{column}
+%-----------------------------------------------------------------------------
+
+\begin{column}{\onecolwid}
+
+\begin{block}{Sparse Recovery}
+
+\begin{itemize}
+ \item Solving for $A x = b$ when $A$ is non-degenerate is possible if
+ \begin{itemize}
+ \item $A$ is {\bf almost invertible}
+ \item $x$ is {\bf sparse}
+ \end{itemize}
+ \item If $x$ is solution to $\min L(x)$ where
+ $L$ is convex, then~\cite{Negahban:2009}~solve for:
+ \begin{equation*}
+ \min_x L(x) + \lambda \| x\|
+ \end{equation*}
+\end{itemize}
+\end{block}
+
+\begin{theorem}
+ {\bf Assumptions}:
+ \begin{itemize}
+ \item $f$ and $1-f$ are log-concave with log-gradient bounded by
+ $\frac{1}{\alpha}$
+ \item $\nabla^2 {\cal L}$ verifies the $(S,\gamma)$-{\bf
+ RE} condition
+ \vspace{1cm}
+\end{itemize} {\bf Algorithm}:
+ \begin{itemize}
+ \item Solve MLE program with $\lambda = 2\sqrt{\frac{\log m}{\alpha n}}$
+ \begin{framed}
+ \begin{equation*}
+ \hat \theta_i \in \arg \max_{\theta} {\cal L}_i(\theta_i | x^1,
+ \dots x^n) - \lambda \|\theta_i\|_1
+ \end{equation*}
+ \end{framed}
+ \end{itemize}
+ \vspace{1cm}
+ {\bf Guarantee}
+ With high probability:
+ \begin{framed}
+ \begin{equation*}
+ \|\hat \theta - \theta^*\|_2 \leq \frac{6}{\gamma} \sqrt{\frac{s \log
+ m}{\alpha n}}
+ \end{equation*}
+ \end{framed}
+ where $s$ is degree of node, $m$ is number of nodes, $n$ is the number of
+ observations
+\end{theorem}
+
+\begin{block}{Restricted Eigenvalue Condition}
+ {\bf Definition}
+ \begin{itemize}
+ \item $C(S) \equiv \{ X :\|X_{\bar S}\|_1 \leq 3 \|X\|_1\}$
+ \item Matrix $A$ verifies the $(\gamma, S)$-{(\bf RE)} condition if:
+ $$\forall X \in C({\cal S}), X^T A X \geq \gamma \|X\|_2^2$$
+ \end{itemize}
+
+ \vspace{1cm}
+ {\bf Hessian $\mapsto$ Gram Matrix}
+ \begin{itemize}
+ \item If $f$ and $1-f$ are $c$-strictly log-convex, we can replace the
+ condition on the $\nabla^2 {\cal L}$ by the same condition on the Gram
+ matrix $X^T X$.
+ \end{itemize}
+ \vspace{1cm}
+ {\bf Hessian $\mapsto$ Expected Hessian}
+ \begin{itemize}
+ \item If $\mathbb{E}[A]$ verifies the $(S, \gamma)$-{(\bf RE)} condition,
+ then $A$ verifies the $(S, \gamma/2)$-{(\bf RE)}
+ condition~\cite{vandegeer:2009}
+ \end{itemize}
+
+\end{block}
+
+\end{column} % End of the second column
+
+%-----------------------------------------------------------------------------
+\begin{column}{\sepwid}\end{column} % Empty spacer column
+%-----------------------------------------------------------------------------
+\begin{column}{\onecolwid} % The third column
+ \begin{block}{Experimental validation}
+ \begin{figure}
+ \centering
+ \includegraphics[scale=1.2]{../images/watts_strogatz.pdf}
+ \caption{Watts-Strogatz, $300$ nodes, $4500$ edges, uniform edge weights,
+ constant $p_{init}$}
+ \end{figure}
+ \end{block}
+
+
+\begin{block}{Conclusion}
+ \begin{itemize}
+ \item Introduce Generalized Linear Casacade model
+ \item Better finite sample guarantees~\cite{Netrapalli:2012, Abrahao:13,
+ Daneshmand:2014}
+ \item Interpretable conditions on Hessian
+ \item Lower bound+approximately sparse case developed in full
+ paper~\cite{Pouget:2015}
+ \end{itemize}
+\end{block}
+
+%-----------------------------------------------------------------------------
+% REFERENCES
+%-----------------------------------------------------------------------------
+
+\begin{block}{References}
+ {\scriptsize
+ \bibliography{../../paper/sparse}
+\bibliographystyle{plain}}
+\end{block}
+
+%-----------------------------------------------------------------------------
+
+\end{column} % End of the third column
+
+\end{columns} % End of all the columns in the poster
+
+\end{frame} % End of the enclosing frame
+
+
+
+\end{document}
diff --git a/poster/images/SEASLogo_RGB.png b/poster/images/SEASLogo_RGB.png
new file mode 100644
index 0000000..e29fc54
--- /dev/null
+++ b/poster/images/SEASLogo_RGB.png
Binary files differ
diff --git a/src/algorithms.py b/src/algorithms.py
index 24a63f3..43c6721 100644
--- a/src/algorithms.py
+++ b/src/algorithms.py
@@ -38,7 +38,7 @@ def recovery_passed_function(G, cascades, floor_cstt, passed_function,
passed_function should have similar structure to ones in convex_optimation
"""
G_hat = cascade_creation.InfluenceGraph(max_proba=None)
- G_hat.add_nodes_from(G.nodes())
+ G_hat.add_nodes_from(G.nodes())
f_x, f_xz = passed_function(*args, **kwargs)
@@ -83,8 +83,8 @@ def correctness_measure(G, G_hat, print_values=True):
print("Precision: {}".format(precision))
print("Recall: {}".format(recall))
print("F1 score: {}".format(f1_score))
- print("Fall Out: {}".format(fall_out))
- print("l2_norm: {}".format(norm))
+ print("Fall Out: {}".format(fall_out))
+ print("l2_norm: {}".format(norm))
return fp, fn, tp, tn
diff --git a/src/cascade_creation.py b/src/cascade_creation.py
index cdf7484..714c120 100644
--- a/src/cascade_creation.py
+++ b/src/cascade_creation.py
@@ -65,7 +65,8 @@ class InfluenceGraph(nx.DiGraph):
if not hasattr(self, '_mat'):
if self.min_proba is None or self.max_proba is None:
print("You forgot to initialize the min and max proba")
- self._mat = np.zeros((self.number_of_nodes(), self.number_of_nodes()))
+ self._mat = np.zeros((self.number_of_nodes(),
+ self.number_of_nodes()))
else:
self._mat = self.max_proba * np.random.rand(len(self), len(self)
) * np.asarray(nx.adjacency_matrix(self).todense().T)
@@ -73,7 +74,8 @@ class InfluenceGraph(nx.DiGraph):
print("adding sparse edges to the graph")
#Adding sparse non-edges to the graph!
self._mat += .1 * np.random.rand(len(self), len(self)
- ) * np.random.binomial(1, p=.33, size=(len(self), len(self)))
+ ) * np.random.binomial(1, p=.33, size=(len(self),
+ len(self)))
return self._mat
@property
diff --git a/src/convex_optimization.py b/src/convex_optimization.py
index 0d506e1..000143f 100644
--- a/src/convex_optimization.py
+++ b/src/convex_optimization.py
@@ -33,7 +33,7 @@ def sparse_recovery(lbda, n_cascades):
y = lbda * theta_.norm(1) - 1./n_cascades*(
(w).dot(tensor.log(1-tensor.exp(M.dot(theta_))))
+ (1-w).dot(tensor.dot(M, theta_))
- )
+ )
z = tensor.row().T
z_ = z.flatten()
@@ -134,7 +134,7 @@ def test():
A = cascade_creation.generate_cascades(G, .1, 500)
M_val, w_val = cascade_creation.icc_matrixvector_for_node(A, 2)
print(len(M_val))
-
+
#Type lasso
if 0:
f_x, f_xz = type_lasso(lbda)
diff --git a/src/make_plots.py b/src/make_plots.py
index c45479e..8970cdf 100644
--- a/src/make_plots.py
+++ b/src/make_plots.py
@@ -54,7 +54,7 @@ def plot_watts_strogatz_graph():
plt.clf()
fig = plt.figure(1)
labels = [50, 100, 500, 1000, 2000, 5000]
- x = [np.log(50), np.log(100), np.log(500),
+ x = [np.log(50), np.log(100), np.log(500),
np.log(1000), np.log(2000), np.log(5000)]
sparse_recov = [.25, .32, .7, .82, .89, .92]
max_likel = [.21, .29, .67, .8, .87, .9]
@@ -84,7 +84,7 @@ def plot_barabasi_albert_graph():
plt.clf()
fig = plt.figure(1)
labels = [50, 100, 500, 1000, 2000, 5000]
- x = [np.log(50), np.log(100), np.log(500),
+ x = [np.log(50), np.log(100), np.log(500),
np.log(1000), np.log(2000), np.log(5000)]
sparse_recov = [.35, .38, .58, .69, .79, .86]
max_likel = [.35, .38, .56, .68, .78, .85]
@@ -188,13 +188,13 @@ def plot_ROC_curve(figure_name):
plt.ylabel("Precision")
plt.grid(color="lightgrey")
- ax.plot(recall_lasso_200, precision_lasso_200, 'ko-',
+ ax.plot(recall_lasso_200, precision_lasso_200, 'ko-',
color="lightseagreen", label="Lasso-200 cascades")
- ax.plot(recall_sparse_200, precision_sparse_200, 'ko-',
+ ax.plot(recall_sparse_200, precision_sparse_200, 'ko-',
color="k", label="Our Method-200 cascades")
- ax.plot(recall_lasso_50, precision_lasso_50, 'ko-',
+ ax.plot(recall_lasso_50, precision_lasso_50, 'ko-',
color="orange", label="Lasso-50 cascades")
- ax.plot(recall_sparse_50, precision_sparse_50, 'ko-',
+ ax.plot(recall_sparse_50, precision_sparse_50, 'ko-',
color="cornflowerblue", label="Our Method-50 cascades")
plt.legend(loc="upper right", fontsize=14)
plt.savefig("../paper/figures/"+"ROC_curve.pdf")
@@ -253,9 +253,9 @@ if __name__=="__main__":
#algorithms.greedy_prediction)
#convex_optimization.type_lasso)
if 0:
- compute_graph("../datasets/kronecker_graph_256_cross.txt",
+ compute_graph("../datasets/kronecker_graph_256_cross.txt",
n_cascades=50, lbda=0., min_proba=.2, max_proba=.7,
passed_function=
- convex_optimization.sparse_recovery,
+ convex_optimization.sparse_recovery,
#convex_optimization.type_lasso,
- sparse_edges=True) \ No newline at end of file
+ sparse_edges=True)
generated by cgit v1.2.3-70-g09d2 (git 2.52.0) at 2025-12-21 15:02:30 +0000