2.5k citations · 3.6k across the 7 of their papers we have counts for
4 papers · 1 filter
GraphLab: A New Framework For Parallel Machine Learning
Yucheng Low, Joseph E. Gonzalez, Aapo Kyrola +3
Designing and implementing efficient, provably correct parallel machine learning (ML) algorithms is challenging. Existing high-level parallel abstractions like MapReduce are insuff…
GraphLab: A Distributed Framework for Machine Learning in the Cloud
Yucheng Low, Joseph Gonzalez, Aapo Kyrola +2
Machine Learning (ML) techniques are indispensable in a wide range of fields. Unfortunately, the exponential increase of dataset sizes are rapidly extending the runtime of sequenti…
Parallel Coordinate Descent for L1-Regularized Loss Minimization
Joseph K. Bradley, Aapo Kyrola, Danny Bickson +1
We propose Shotgun, a parallel coordinate descent algorithm for minimizing L1-regularized losses. Though coordinate descent seems inherently sequential, we prove convergence bounds…
GraphLab: A New Framework for Parallel Machine Learning
Yucheng Low, Joseph Gonzalez, Aapo Kyrola +3
Designing and implementing efficient, provably correct parallel machine learning (ML) algorithms is challenging. Existing high-level parallel abstractions like MapReduce are insuff…