no code implementations • 26 Mar 2020 • Fatemehsadat Mireshghallah, Mohammadkazem Taram, Ali Jalali, Ahmed Taha Elthakeb, Dean Tullsen, Hadi Esmaeilzadeh
We formulate this problem as a gradient-based perturbation maximization method that discovers this subset in the input feature space with respect to the functionality of the prediction model used by the provider.
no code implementations • 14 May 2013 • Ali Jalali, Santanu Kolay, Peter Foldes, Ali Dasdan
This trade-off between reachability and performance illustrates a need for a forecasting system that can quickly predict/estimate (with good accuracy) this trade-off.
no code implementations • 14 May 2013 • Kuang-Chih Lee, Ali Jalali, Ali Dasdan
Today, billions of display ad impressions are purchased on a daily basis through a public auction hosted by real time bidding (RTB) exchanges.
no code implementations • 30 Mar 2012 • Ali Jalali, Javad Azimi, Xiaoli Fern, Ruofei Zhang
The exploration phase aims to select samples that shrink the search space as much as possible.
no code implementations • NeurIPS 2011 • Ali Jalali, Christopher C. Johnson, Pradeep K. Ravikumar
In this paper, we address the problem of learning the structure of a pairwise graphical model from samples in a high-dimensional setting.
no code implementations • 25 Apr 2011 • Yudong Chen, Ali Jalali, Sujay Sanghavi, Huan Xu
This paper considers the problem of clustering a partially observed unweighted graph---i. e., one where for some node pairs we know there is an edge between them, for some others we know there is no edge, and for the remaining we do not know whether or not there is an edge.
no code implementations • NeurIPS 2010 • Ali Jalali, Sujay Sanghavi, Chao Ruan, Pradeep K. Ravikumar
However, these papers also caution that the performance of such block-regularized methods are very dependent on the {\em extent} to which the features are shared across tasks.