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authorjeanpouget-abadie <jean.pougetabadie@gmail.com>2015-05-07 13:53:36 -0400
committerjeanpouget-abadie <jean.pougetabadie@gmail.com>2015-05-07 13:53:36 -0400
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\subsection{Proof for different lemmas}
\subsubsection{Bounded gradient}
+
+\begin{proof}
+The gradient of $\mathcal{L}$ is given by:
+\begin{multline*}
+ \nabla \mathcal{L}(\theta^*) =
+ \frac{1}{|\mathcal{T}|}\sum_{t\in \mathcal{T}}x^t\bigg[
+ x_i^{t+1}\frac{f'}{f}(\inprod{\theta^*}{x^t})\\
+ - (1-x_i^{t+1})\frac{f'}{1-f}(\inprod{\theta^*}{x^t})\bigg]
+\end{multline*}
+
+Let $\partial_j \mathcal{L}(\theta)$ be the $j$-th coordinate of
+$\nabla\mathcal{L}(\theta^*)$. Writing
+$\partial_j\mathcal{L}(\theta^*)
+= \frac{1}{|\mathcal{T}|}\sum_{t\in\mathcal{T}} Y_t$ and since
+$\E[x_i^{t+1}|x^t]= f(\inprod{\theta^*}{x^t})$, we have that $\E[Y_{t+1}|Y_t]
+= 0$. Hence $Z_t = \sum_{k=1}^t Y_k$ is a martingale.
+
+Using assumption (LF), we have almost surely $|Z_{t+1}-Z_t|\leq
+\frac{1}{\alpha}$ and we can apply Azuma's inequality to $Z_t$:
+\begin{displaymath}
+ \P\big[|Z_{\mathcal{T}}|\geq \lambda\big]\leq
+ 2\exp\left(\frac{-\lambda^2\alpha}{2n}\right)
+\end{displaymath}
+
+Applying a union bound to have the previous inequality hold for all coordinates
+of $\nabla\mathcal{L}(\theta)$ implies:
+\begin{align*}
+ \P\big[\|\nabla\mathcal{L}(\theta^*)\|_{\infty}\geq \lambda \big]
+ &\leq 2m\exp\left(\frac{-\lambda^2n\alpha}{2}\right)
+\end{align*}
+Choosing $\lambda\defeq 2\sqrt{\frac{\log m}{\alpha n^{1-\delta}}}$ concludes
+the proof.
+\end{proof}
+
\subsubsection{Approximate sparsity proof}
\subsubsection{RE with high probability}
-\subsection{Other continuous time processes binned to ours: prop. hazards model}
+\subsection{Other continuous time processes binned to ours: proportional
+hazards model}
\subsection{Irrepresentability vs. Restricted Eigenvalue Condition}
In the words and notation of Theorem 9.1 in \cite{vandegeer:2009}: