13 citations · 15 across the 5 of their papers we have counts for
5 papers
Sharper Bounds for Chebyshev Moment Matching, with Applications
Cameron Musco, Christopher Musco, Lucas Rosenblatt +1
We study the problem of approximately recovering a probability distribution given noisy measurements of its Chebyshev polynomial moments. This problem arises broadly across algorit…
Faster Spectral Density Estimation and Sparsification in the Nuclear Norm
Yujia Jin, Ishani Karmarkar, Christopher Musco +2
We consider the problem of estimating the spectral density of the normalized adjacency matrix of an -node undirected graph. We provide a randomized algorithm that, with $O(nε^{-…
Moments, Random Walks, and Limits for Spectrum Approximation
Yujia Jin, Christopher Musco, Aaron Sidford +1
We study lower bounds for the problem of approximating a one dimensional distribution given (noisy) measurements of its moments. We show that there are distributions on th…
Regularized spectral methods for clustering signed networks
Mihai Cucuringu, Apoorv Vikram Singh, Déborah Sulem +1
We study the problem of -way clustering in signed graphs. Considerable attention in recent years has been devoted to analyzing and modeling signed graphs, where the affinity mea…
On Euclidean -Means Clustering with -Center Proximity
Amit Deshpande, Anand Louis, Apoorv Vikram Singh
-means clustering is NP-hard in the worst case but previous work has shown efficient algorithms assuming the optimal -means clusters are \emph{stable} under additive or multi…