136 citations · 190 across the 18 of their papers we have counts for
22 papers
Expert-guided Regularization via Distance Metric Learning
Shouvik Mani, Mehdi Maasoumy, Sina Pakazad +1
High-dimensional prediction is a challenging problem setting for traditional statistical models. Although regularization improves model performance in high dimensions, it does not…
Effects of Risk on Privacy Contracts for Demand-Side Management
Lillian J. Ratliff, Carlos Barreto, Roy Dong +3
As smart meters continue to be deployed around the world collecting unprecedented levels of fine-grained data about consumers, we need to find mechanisms that are fair to both, (1)…
Quantifying the Utility-Privacy Tradeoff in the Smart Grid
Roy Dong, Alvaro A. Cárdenas, Lillian J. Ratliff +2
The modernization of the electrical grid and the installation of smart meters come with many advantages to control and monitoring. However, in the wrong hands, the data might pose…
Privacy and Customer Segmentation in the Smart Grid
Lillian J. Ratliff, Roy Dong, Henrik Ohlsson +2
In the electricity grid, networked sensors which record and transmit increasingly high-granularity data are being deployed. In such a setting, privacy concerns are a natural consid…
Sparse phase retrieval via group-sparse optimization
Fabien Lauer, Henrik Ohlsson
This paper deals with sparse phase retrieval, i.e., the problem of estimating a vector from quadratic measurements under the assumption that few components are nonzero. In particul…
Analysis of A Nonsmooth Optimization Approach to Robust Estimation
Laurent Bako, Henrik Ohlsson
In this paper, we consider the problem of identifying a linear map from measurements which are subject to intermittent and arbitarily large errors. This is a fundamental problem in…