activity
20202026
most citedA gradient sampling method with complexity guarantees for Lipschitz functions in high and low dimensions

3 citations · 9 across the 9 of their papers we have counts for

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6 papers · 1 filter

cs.DS2024

Improving the Bit Complexity of Communication for Distributed Convex Optimization

Mehrdad Ghadiri, Yin Tat Lee, Swati Padmanabhan +3

We consider the communication complexity of some fundamental convex optimization problems in the point-to-point (coordinator) and blackboard communication models. We strengthen kno…

cs.DS2023

Fast Algorithms for Separable Linear Programs

Sally Dong, Gramoz Goranci, Lawrence Li +2

In numerical linear algebra, considerable effort has been devoted to obtaining faster algorithms for linear systems whose underlying matrices exhibit structural properties. A promi…

cs.DS2023

Faster Min-Cost Flow and Approximate Tree Decomposition on Bounded Treewidth Graphs

Sally Dong, Guanghao Ye

We present an algorithm for min-cost flow in graphs with vertices and edges, given a tree decomposition of width and size , and polynomially bounded, integral edge c…

cs.DS2022

Nested Dissection Meets IPMs: Planar Min-Cost Flow in Nearly-Linear Time

Sally Dong, Yu Gao, Gramoz Goranci +4

We present a nearly-linear time algorithm for finding a minimum-cost flow in planar graphs with polynomially bounded integer costs and capacities. The previous fastest algorithm fo…

cs.DS2020★ 2 cited

A Nearly-Linear Time Algorithm for Linear Programs with Small Treewidth: A Multiscale Representation of Robust Central Path

Sally Dong, Yin Tat Lee, Guanghao Ye

Arising from structural graph theory, treewidth has become a focus of study in fixed-parameter tractable algorithms in various communities including combinatorics, integer-linear p…

cs.DS2020★ 3 cited

Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time

Jerry Li, Guanghao Ye

Robust covariance estimation is the following, well-studied problem in high dimensional statistics: given samples from a -dimensional Gaussian $\mathcal{N}(\boldsymbol{0}, Σ…