885 citations · 2.1k across the 60 of their papers we have counts for
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Speeding Up Distributed Machine Learning Using Codes
Kangwook Lee, Maximilian Lam, Ramtin Pedarsani +2
Codes are widely used in many engineering applications to offer robustness against noise. In large-scale systems there are several types of noise that can affect the performance of…
Sparse PCA via Bipartite Matchings
Megasthenis Asteris, Dimitris Papailiopoulos, Anastasios Kyrillidis +1
We consider the following multi-component sparse PCA problem: given a set of data points, we seek to extract a small number of sparse components with disjoint supports that jointly…
On the Worst-Case Approximability of Sparse PCA
Siu On Chan, Dimitris Papailiopoulos, Aviad Rubinstein
It is well known that Sparse PCA (Sparse Principal Component Analysis) is NP-hard to solve exactly on worst-case instances. What is the complexity of solving Sparse PCA approximate…
Parallel Correlation Clustering on Big Graphs
Xinghao Pan, Dimitris Papailiopoulos, Samet Oymak +3
Given a similarity graph between items, correlation clustering (CC) groups similar items together and dissimilar ones apart. One of the most popular CC algorithms is KwikCluster: a…
Perturbed Iterate Analysis for Asynchronous Stochastic Optimization
Horia Mania, Xinghao Pan, Dimitris Papailiopoulos +3
We introduce and analyze stochastic optimization methods where the input to each gradient update is perturbed by bounded noise. We show that this framework forms the basis of a uni…