961 citations · 999 across the 6 of their papers we have counts for
7 papers
Matrix Computations and Optimization in Apache Spark
Reza Bosagh Zadeh, Xiangrui Meng, Aaron Staple +6
We describe matrix computations available in the cluster programming framework, Apache Spark. Out of the box, Spark provides abstractions and implementations for distributed matric…
MLlib: Machine Learning in Apache Spark
Xiangrui Meng, Joseph Bradley, Burak Yavuz +13
Apache Spark is a popular open-source platform for large-scale data processing that is well-suited for iterative machine learning tasks. In this paper we present MLlib, Spark's ope…
Implementing Randomized Matrix Algorithms in Parallel and Distributed Environments
Jiyan Yang, Xiangrui Meng, Michael W. Mahoney
In this era of large-scale data, distributed systems built on top of clusters of commodity hardware provide cheap and reliable storage and scalable processing of massive data. Here…
Quantile Regression for Large-scale Applications
Jiyan Yang, Xiangrui Meng, Michael W. Mahoney
Quantile regression is a method to estimate the quantiles of the conditional distribution of a response variable, and as such it permits a much more accurate portrayal of the relat…
Low-distortion Subspace Embeddings in Input-sparsity Time and Applications to Robust Linear Regression
Xiangrui Meng, Michael W. Mahoney
Low-distortion embeddings are critical building blocks for developing random sampling and random projection algorithms for linear algebra problems. We show that, given a matrix $A…
The Fast Cauchy Transform and Faster Robust Linear Regression
Kenneth L. Clarkson, Petros Drineas, Malik Magdon-Ismail +3
We provide fast algorithms for overconstrained regression and related problems: for an input matrix and vector , in time we…