7 citations · 21 across the 8 of their papers we have counts for
12 papers
Robust Regression Revisited: Acceleration and Improved Estimation Rates
Arun Jambulapati, Jerry Li, Tselil Schramm +1
We study fast algorithms for statistical regression problems under the strong contamination model, where the goal is to approximately optimize a generalized linear model (GLM) give…
Stochastic Bias-Reduced Gradient Methods
Hilal Asi, Yair Carmon, Arun Jambulapati +2
We develop a new primitive for stochastic optimization: a low-bias, low-cost estimator of the minimizer of any Lipschitz strongly-convex function. In particular, we use a…
Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss
Yair Carmon, Arun Jambulapati, Yujia Jin +1
We characterize the complexity of minimizing for convex, Lipschitz functions . For non-smooth functions, existing methods require $O(Nε^{-2…
Semi-Streaming Bipartite Matching in Fewer Passes and Optimal Space
Sepehr Assadi, Arun Jambulapati, Yujia Jin +2
We provide -pass semi-streaming algorithms for computing -approximate maximum cardinality matchings in bipartite graphs. Our most efficient methods ar…
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing
Arun Jambulapati, Jerry Li, Kevin Tian
We develop two methods for the following fundamental statistical task: given an -corrupted set of samples from a -dimensional sub-Gaussian distribution, return an approxi…
Acceleration with a Ball Optimization Oracle
Yair Carmon, Arun Jambulapati, Qijia Jiang +4
Consider an oracle which takes a point and returns the minimizer of a convex function in an ball of radius around . It is straightforward to show that rough…