170 citations · 909 across the 66 of their papers we have counts for
6 papers · 1 filter
Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm
Deanna Needell, Nathan Srebro, Rachel Ward
We obtain an improved finite-sample guarantee on the linear convergence of stochastic gradient descent for smooth and strongly convex objectives, improving from a quadratic depende…
Recovery guarantees for exemplar-based clustering
Abhinav Nellore, Rachel Ward
For a certain class of distributions, we prove that the linear programming relaxation of -medoids clustering---a variant of -means clustering where means are replaced by exem…
Interpolation via weighted minimization
Holger Rauhut, Rachel Ward
Functions of interest are often smooth and sparse in some sense, and both priors should be taken into account when interpolating sampled data. Classical linear interpolation method…
Testing goodness-of-fit for logistic regression
Mark Tygert, Rachel Ward
Explicitly accounting for all applicable independent variables, even when the model being tested does not, is critical in testing goodness-of-fit for logistic regression. This can…
Completing Any Low-rank Matrix, Provably
Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi +1
Matrix completion, i.e., the exact and provable recovery of a low-rank matrix from a small subset of its elements, is currently only known to be possible if the matrix satisfies a…
Significance testing without truth
William Perkins, Mark Tygert, Rachel Ward
A popular approach to significance testing proposes to decide whether the given hypothesized statistical model is likely to be true (or false). Statistical decision theory provides…