273 citations · 1.6k across the 53 of their papers we have counts for
4 papers · 1 filter
Improved Distributed Principal Component Analysis
Maria-Florina Balcan, Vandana Kanchanapally, Yingyu Liang +1
We study the distributed computing setting in which there are multiple servers, each holding a set of points, who wish to compute functions on the union of their point sets. A key…
Scalable Kernel Methods via Doubly Stochastic Gradients
Bo Dai, Bo Xie, Niao He +4
The general perception is that kernel methods are not scalable, and neural nets are the methods of choice for nonlinear learning problems. Or have we simply not tried hard enough f…
A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning
Aurélien Bellet, Yingyu Liang, Alireza Bagheri Garakani +2
Learning sparse combinations is a frequent theme in machine learning. In this paper, we study its associated optimization problem in the distributed setting where the elements to b…
Robust Hierarchical Clustering
Maria-Florina Balcan, Yingyu Liang, Pramod Gupta
One of the most widely used techniques for data clustering is agglomerative clustering. Such algorithms have been long used across many different fields ranging from computational…