58 citations · 178 across the 12 of their papers we have counts for
5 papers · 1 filter
The Data Station: Combining Data, Compute, and Market Forces
Raul Castro Fernandez, Kyle Chard, Ben Blaiszik +7
This paper introduces Data Stations, a new data architecture that we are designing to tackle some of the most challenging data problems that we face today: access to sensitive data…
Fast and Reliable Missing Data Contingency Analysis with Predicate-Constraints
Xi Liang, Zechao Shang, Aaron J. Elmore +2
Today, data analysts largely rely on intuition to determine whether missing or withheld rows of a dataset significantly affect their analyses. We propose a framework that can produ…
Machine Learning enabled Spectrum Sharing in Dense LTE-U/Wi-Fi Coexistence Scenarios
Adam Dziedzic, Vanlin Sathya, Muhammad Iqbal Rochman +2
The application of Machine Learning (ML) techniques to complex engineering problems has proved to be an attractive and efficient solution. ML has been successfully applied to sever…
Analysis of Random Perturbations for Robust Convolutional Neural Networks
Adam Dziedzic, Sanjay Krishnan
Recent work has extensively shown that randomized perturbations of neural networks can improve robustness to adversarial attacks. The literature is, however, lacking a detailed com…
Understanding and Optimizing Packed Neural Network Training for Hyper-Parameter Tuning
Rui Liu, Sanjay Krishnan, Aaron J. Elmore +1
As neural networks are increasingly employed in machine learning practice, how to efficiently share limited training resources among a diverse set of model training tasks becomes a…