22 citations · 68 across the 10 of their papers we have counts for
13 papers
Version Reconciliation for Collaborative Databases
Nalin Ranjan, Zechao Shang, Aaron J. Elmore +1
We propose MindPalace, a prototype of a versioned database for efficient collaborative data management. MindPalace supports offline collaboration, where users work independently wi…
CIAO: An Optimization Framework for Client-Assisted Data Loading
Cong Ding, Dixin Tang, Xi Liang +2
Data loading has been one of the most common performance bottlenecks for many big data applications, especially when they are running on inefficient human-readable formats, such as…
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…
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…
Band-limited Training and Inference for Convolutional Neural Networks
Adam Dziedzic, John Paparrizos, Sanjay Krishnan +2
The convolutional layers are core building blocks of neural network architectures. In general, a convolutional filter applies to the entire frequency spectrum of the input data. We…